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User`s Guide to COSI-CORR Co-registration of Optically Sensed

1. Fiducial Points Fiducial Measures Affine transformation coefficients from Camera to Image X al al a2 y Y b0 b1 b2 y al 5942 0640865 al 0 0284958 a2 47 6210981 b0 5773 7682321 b1 47 6354779 b2 0 0397662 Affine transformation coefficients from Image to Camera XK a0 al x a2 y Y b0 b1 b2 y a0 121 1030806 a1 0 0000175 a2 0 0209927 bO 124 8504385 b1 0 0209991 b2 0 0000126 Lense Radial Radial Measures Ko 74567D 005 K1 30855D 009 K2 56084D 013 Lense Tangential Tangential Measures Po op P1 op P2 op Atmospheric Correction Output Select Interior Orientation File Not Selected Figure 3 Interior Orientation tool rotation angles w k and may be seen as the roll pitch and yaw of the focal plane These six parameters are determined using space resection by collinearity Ayoub et al 2007 Wolf amp Dewitt 2000 1 Interior Orientation Select the file obtained during the Interior Orientation of the camera Sec 4 1 2 GCPS File Select the file containing the GCPS This file can be obtained from Sec 6 2 or edited manually It is an ASCII file which presents data in an array form One GCP per line with a line composed of longitude decimal degree latitude decimal degree altitude meter X pixel Y pixel SNR 0 to 1 other SNR represents the weight of each GCP in the global EO computation The file must contains at least three
2. References S Leprince S Barbot F Ayoub and J P Avouac Automatic and Precise Ortho rectification Coregistration and Subpixel Correlation of Satellite Images Application to Ground Deformation Measurements IEEE Trans Geosci Remote Sensing vol 45 no 6 pp 1529 1558 2007 F Ayoub S Leprince and J P Avouac Co registration and Correlation of Aerial Photographs for Ground Deformation Measurements submitted 2007 N Van Puymbroeck R Michel R Binet J P Avouac and J Taboury Measuring earthquakes from optical satellite images Applied Optics vol 39 no 20 pp 3486 to 3494 2000 P R Wolf and B A Dewitt Elements of Photogrammetry with Applications in GIS 3rd ed Mc Graw Hill 2000 A Buades B Coll and J M Morel NonLocal Image and Movie Denoising International Journal of Com puter Vision vol 76 no 2 pp 123 to 139 2008 A Buades B Coll and J M Morel The staircasing effect in neighborhood filters and its solution IEEE transactions on Image Processing vol 15 no 6 pp 1499 to 1505 2006 B Goossens H Luong A Pizurica and W Philips An Improved Non Local Denoising Algorithm Pro ceedings of the 2008 International Workshop on Local and Non Local Approximation in Image Processing Lausanne Switzerland 2008 S Zimmer S Didas and J Weickert A Rotationally Invariant Block Matching Strategy Improving Image Denoising With Non Local Means Proceeding
3. Select Reference Image D StudpCase Ortho_Image_1 Select DEM File D StudpCase DEM Select 10 File D StudyCaseM Image 2 t t Select GCPS Tied Points File D NStudyCaseMpts Raw Img2 with Ortho Imgl pts Nb Iteration 5 Resampling Kernel Sinc Options Correlator Engine Frequential v Options v Weight GCPS with Correlation SNR v Dynamic Display of Optimization Select Optimized GCPS D StudyCaseN ptimized GCPS Image 2 t t Figure 7 GCPS optimization parameters selection tool poor quality content that may biased the correlation if optimized Although rarely used this option can be useful when dealing with heavy snow or heavy cloud cover DX DY DZ are used to account for a ground displacement sustained at the GCP location They refer respectively to the displacement in Easting Northing and Elevation in meter currently the Elevation displacement is not used If values are entered the GCP will be optimized in order to co register the images while accounting for the displacement entered at the GCP location e Tie points file This is a file whose format is x ref y ref x raw y raw and is usually generated with the ENVI tie points selection tool Sec 6 1 or edited manually The reference image and raw image used for the tie points selection must be the same as the ones entered in the GCPS optimization windows Tie points will be converted to GCPS prior to optimization Note that if
4. buttons Size and center position of the selected box can be changed with Stack Length odd and Stack Width odd fields and Position on fault buttons The simple arrow button moves the box center to the next pixel on the fault whereas the double arrows button moves to the next 20ieth pixel on the fault 34 71 1 North South Chichi Displacement Bo File Options View Stack 1 Stack 8 _Add Remove 44 PosiiononFaut P pp x 278 v 128 Stack Length odd 101 Stack Width odd 31 Accept lt Band p Curent Band North South Left Fit From 46 To 10 RiohtFit From 5 To 50 Fit Stack Offset 7 27430 Sigma 0 283568 Figure 21 Profiles stacking tool Stacking Boxes Visualization To visualize the stack boxes select View gt Stack Visualization and open the ROI tool as stack boxes are displayed through the ENVI ROI tool Close all open ROIs before visualizing the stack boxes as open ROIs will be first deleted Profile projection By default profiles are in the file band projection i e in the E W and N S projection for a regular correlation file Profiles can also be projected in the fault parallel and fault normal directions using Options gt Profiles Projection It is assumed for the Parallel Normal projection to receive a two or more bands file with first and second bands representing the E W and N
5. GH Map Into Gg ConelationSeismo gt East West Gray Scale RGB Color Selected Band North South Memory6 Figure 19 Destripping tool corrected image e Ratio Arrow Length Ratio to control the length display of the vectors e Unit Enter the unit name that is displayed on the vector field legend e Vector Field Options The list displays all the data entered on the current display Select the entry of interest to have access to the following options Vector Field Name Select the name that will be displayed in the list Average Window Size Option available only to ENVI data files Determines the window odd size centered on the vector location to average the values in the file Step Option available only to ENVI data files Step in pixel between two displayed vectors Performs the decimation of a displacement field if more than 1 Line Thickness Ratio to determine the thickness of the displayed vectors Note Saving the vector field as an ENVI Layer will not work in ENVI 4 0 due to an internal ENVI error 10 5 Stacking Profiles In the context of seismotectonics this tool Tools gt Stacking allows to stack profiles across the fault on the correlation file to retrieve the fault step Prior to stacking profiles a mapping of the fault is necessary 1 Using the ENVI ROI tool with the polyline selection option ROI_Type gt Polyline map precisely t
6. R mi Michel and Renaud Binet for their insightful comments and their early work in the field of sub pixel image registration and correlation Van Puymbroeck et al 2000 We also thank Sylvain Barbot for his work on the SPOT 5 ancillary data Pablo Muse for the UNIX module installation guide and David Fanning for some IDL functions The COSLCorr development team asks that you cite S Leprince S Barbot F Ayoub and J P Avouac Automatic and Precise Ortho rectification Coregistration and Subpixel Correlation of Satellite Images Application to Ground Deformation Measurements IEEE Transactions on Geoscience and Remote Sensing vol 45 no 6 pp 1529 1558 2007 and if working with aerial images F Ayoub S Leprince and J P Avouac Co registration and Correlation of Aerial Photographs for Ground Deformation Measurements Submitted 2007 The developers also request that in your oral presentations and in your paper acknowledgements you indicate the use of COSI Corr the authors and website http www tectonics caltech edu slip his tory spot coseis index htm l 1 6 Disclaimer NONEXCLUSIVE NON TRANSFERABLE LICENSE AGREEMENT FOR RESEARCH PURPOSES ONLY FOR COSI Corr Software Co registration of Optically Sensed Images and Correlation The California Institute of Technology CIT will provide you a not for profit institution LICENSEE with the Co registration of Optically Sensed Images and Correlation Software COSI Corr Soft
7. S displacements a correlation file typically For each stacked profile the fit range can be customized on the left and right part of the profile as well as on the available bands The range can be changed by moving the green rulers with the mouse or by entering range values in the appropriate fields Output A stack project can be saved restored using File gt Save Stack Restore Stack Note that only the stacks size positions and fit ranges will be saved You will be asked to enter the image and fault file when restoring When done with adjusting the profiles two options are available to export them e File gt Export gt Fault Displacement will save the fault offset measure location geographic coordi nates its values E W N S or Parallel Normal depending on the chosen projection and the sigmas e File gt Export gt Full Stack Information will save in addition the details of each stacks box size profiles stacked The possibility of weighting the sigmas is offered before exporting the data For example if the measures in the correlation file are not totally independent the sigmas must be weighted accordingly in order to correctly reflects the sigma on the offset measures 35 Matrices Interdistances Input DK Select Matrices D StudyCase Matrice_Image_1 Cancel Area of interest in mage 1 amp Select X min 0 X max 11617 Leave empty for no limit Y min 0 Y max 11619 Leave empt
8. and install reboot needed the Visual C runtime from Microsoft This download can be found at http www microsoft com downloads details aspx FamilyID 9b2da534 3e03 4391 8a4d 074b9f2bc1bf amp displaylang en Unix Installation Installation on Unix is somewhat more complicated than for Windows Most ENVI users on UNIX systems do not have the rights to change the Customizing ENVI files or to add their own procedures to the ENVI save_add directory Multiple users may indeed be working with the same installation of ENVI so cus tomizing these files may not be allowed by the system administrator To customize ENVI files on a UNIX system without affecting other users perform the following steps 1 Copy the ENVI files envi cfg and e_locate pro to any location you want for example home myusername myEnviConfi For a typical Unix installation these files are located in the installation path may be slightly different on your machine usr local rsi idl_ 6 0 products envi_ 4 0 menu 2 a CSH or TCSH shells Set up environment for ENVI 4 0 and above and modify IDL search path variable IDL Path Add lines to your cshrc or tcshrc file in your home directory to execute the ENVI setup file when you start a new csh or tcsh shell and to add your home directory tree into the IDL file search path This ensures that ENVI finds the files in your home directory before it finds copies in the default installation location w
9. characterize the area sur rounding each data point The choices are limited to 5x5 or 7x7 The default selection is 5x5 Weighting method This selection refers to the method by which the final value is ultimately computed 27 Averaging The denoised value is determined by a simple weighted average of the pixels comprised in the search area This is the default setting Linear regression The denoised value is determined by weighted linear regression of the pixels within the search area 10 1 3 Advanced Filter Parameters Fig 15 Filter Params Advanced Minimum weight value 0 10000000 Minimum amp of weights 6 T Center data point Omit Se Noise parameter Fixed v Weighting type Bisquare v Figure 15 Non Local Means Filter Advanced Parameters Minimum weight value Only used if the Linear regression weighting method is selected otherwise it is ignored Only weights above this threshold will be counted in the minimum number of weights computation This sanity check ensures that very small weights are not counted as part of a valid averaging The default value for this field is 0 1 This value must be a floating point between 0 0 1 0 The closer this parameter is to zero the more the linear regression filtering will occur with the risk of fitting the noise for pixels with very few similar patches in the search area The closer this parameter is to one the less the linear regression filtering will oc
10. name of the GCPS file to be created The format of the GCPS file created is Fig 6 longitude decimal degree latitude decimal degree alti tude meter X pixel Y pixel SNR 0 to 1 OPTI 0 or 1 DX meter DY meter DZ meter SNR set to 1 by default can be changed manually if needed and is used during the orthorectification and the GCPS Optimization OPTI DX DY DZ are used for the GCPS Optimization only See Sec 8 1 Sec 7 for more details 7 GCPS Optimization Even with all the care taken during manual tie points selection converted then to GCPS the orthorectified image usually presents a misregistration with the reference image at the GCP s location To get a better co registration GCPS are refined using the following process 1 Zi The raw image EO aerial Look Angles satellite are computed using the GCPS The raw image is ortho rectified and correlated with the reference image 17 GCPS Image 1 txt Notepad DER File Edit Format View Help File generated the wed Mar 15 18 57 51 2006 GCPS generated from Tied point file D XNstudyCaseWMtpts Raw Img2 with ortho Imgl pts i GeoReferenced image D XStudyCase wortho Image 1 j DEM D studyCase DEM values Easting Northing Altitude x Y weight opti dE dN dA Note Opti dE dN and dA are only used in Gcps optimization 116 506195191 313134931 1173 68518739 2083 9954 1 0000 0 0000 116 494217100 382102952 834 158199
11. the necessity to reorder the fault points to physically follow the fault the ENVI ROI tool save the points line wise The second reason is to define the origin of the fault as it will dictates the fault orientation for measurements made parallel and normal to the fault The parameters are the following 1 Fault Trace ROI Ascii File Select the file generated with the ROI tool when mapping the fault 2 Fault Origin Enter the X and Y pixel coordinates of the first point of the fault given by the Cursor Location Value tool If not selected the first pixel found in the fault trace file will be considered the fault origin which will be the top pixel line wise of the fault trace 3 Oriented Fault File Select the oriented fault profile file name to be created 10 5 2 Stack This tool Tools gt Stacking gt Stack manages the stacking boxes and resulting profiles Fig 21 A stacking box is defined by its width and length which are expressed in pixels and must be odd The box is centered on a pixel belonging to the fault For each selected bands profiles in the box length direction are retrieved and stacked The resulting profile is displayed and the offset at the fault position can be measured using linear fit on the resulting profile Stacking Box Initialization Boxes can be initialized using Options gt Initialize Profile and or can be added or deleted one by one using the Add and Remove
12. the tie points file is edited manually pixels coordinates contained in the file must be expressed with the convention where the first pixel coordinates are 1 1 to stay consistent with the ENVI points selection process e ICP Image Control Points This option is available only for satellite imagery It is a file whose format is z raw y raw The points do not need to be tied to a reference image as the ancillary data are accurate enough to locate them geographically Points will be converted to GCPS prior to optimization This option can be used with SPOT 5 but is not recommended with SPOT 1 4 and ASTER images Unlike the tie points file pixels coordinates must be expressed in a coordinates system where the first pixel coordinates are 0 0 Note that the weighting of the GCPS the OPTI flag and the DX DY and DZ fields are only available through the use of a GCPS file and not a tie points or ICP files 19 6 Optimization Options a Nb Iterations Number of loops that will be executed to optimize the GCPS 5 loops are usually enough to reach stable convergence If the optimized GCPS file report shows that the convergence is not reached the process should be continued Continuation of the process can easily be done by giving as GCP input file the output file where convergence is not reached b Resampling kernel Select the resampling kernel that will be used to resample the raw images patches This option is simil
13. to GCPS transformation tool This function Tie Points GCP gt Tie points to GCPS converts a set of tie points into GCPS Fig 5 1 5 Tie Points File Select the file containing the tie points between the two images The file must be of the form x master y master x slave y slave in pixel This file is typically generated by the Tie Points Tool Sec 6 1 but can be edited manually Reference Image Select the image used as a reference master during the tie points selection The image must have a map information and is typically an orthorectified image The geographic coordinates will be retrieved from its map information DEM File Select a DEM with a valid map information to retrieve the altitude of the GCPS If not entered the altitude will be set to 0 above ellipsoid WGS 84 Offset field If selected this field must receive a file whose first and second bands contain a displacement map of the area in East West and North South direction respectively a correlation map typically The displacement found at the GCP location is retrieved and added to the GCPS file This information will be used in the GCPS optimization Sec 7 as this displacement will be accounted for during the optimization For example a SPOT based displacement map can be used to account for the ground displacement at GCP location while co registering aerial images Ayoub et al 2007 GCPS File Select the
14. will then be kept consistent between the two images In case of an optimization with a shaded DEM the DEM used should be the one used to generate the shaded DEM Ancillary IO file Select the ancillary file for satellite or the Interior Orientation file for aerial of the raw image GCPS tie points ICP e GCPS A GCPS file is the most flexible option This is a file Fig 6 whose format is longi tude decimal degree latitude decimal degree altitude meter X pixel Y pixel SNR 0 to 1 OPTI 0 or 1 DX meter DY meter DZ meter and contains at least three GCPS obtained generally from the Tie points to GCPS tool Sec 6 2 SNR represents the weight of the GCP between 0 and 1 If the confidence is similar for all points all SNR should be equal and different than zero OPTI is a flag indicating whether the GCP is going to be optimized 1 or not 0 A GCP with the OPTI flag set to 0 will be accounted for during the computing of the EO aerial or Look Angle correction satellite but not optimized A typical example where GCPS should not be optimized would be some GPS points located precisely whereas others GCPS are coarsely estimated Another example would be a feature clearly recognizable between the reference image and the raw image during tie points selection but with a surrounding of 18 l GCPS Optimization Select All I np Cancel Select I f D StudpCase Raw_Image_2 elect Image y g m
15. you to send us a clear report of the problems you may encounter 3 Introduction A Typical Processing Chain The driving motivation for implementing COSI Corr was to set up a tool that retrieves co seismic ground displacements from pre and post earthquake images Although the description is aimed at seismo tectonics it can be applied to any other change detection application We describe below the successive steps to achieve precise co registration and derive deformation measurements We assume here that we have two images bracketing a seismic event Before correlation the images must be cleaned from geometric artifacts such as topography and co registered precisely 1 Define the Interior Orientation aerial or Ancillary data satellite of the two images Sec 4 1 5 1 2 Orthorectify the pre earthquake image a Construct a Ground Control Points GCPS file to refine the pre earthquake image georeferencing GCPS are defined either with GPS campaigns or by taking tie points between the image and a geolocalized reference orthorectified image shaded DEM digitalized high resolution map Sec 6 1 The tie points are then converted into GCPS Sec 6 2 using the georeferencing parameters of the reference image and a DEM Those GCPS can be optimized if necessary Sec 7 11 b Compute the mapping matrices to transform the raw pre earthquake image into an orthorectified image and resample it Sec 8 3 Orthorectify the post ear
16. 19 3348 1257 1 0000 0 0000 116 513120127 348595608 1025 86037987 1367 5355 1 0000 0 0000 116 467548671 307670261 1041 29357648 6282 10458 1 0000 0 0000 116 456503467 353732243 891 91973868 7252 4593 1 0000 0 0000 Figure 6 GCPS text file format 3 At each GCP location the GCP ground coordinates are corrected by the ground offset found between the images 4 The process is iterated with the corrected set of GCPS until convergence of the ground offset correction This function Aerial Imagery or Satellite Imagery gt GCPS Optimization gt GCP Optimization opti mizes a raw image GPCS with respect to a reference orthorectified image to achieve a good co registration Fig 7 1 2 Raw Image Select the raw image whose GCPS are going to be optimized Reference Image Select the orthorectified image onto which the raw image will be co registered This image corresponds generally to the first orthorectified image of the pair a shaded DEM or an external orthorectified image The reference must be georeferenced in the UTM projection DEM Select the DEM that will be used to correct the topographic effects during the optimization If selected the DEM must be georeferenced and can be of any projection If not selected the topography will be considered flat at altitude 0 above the ellipsoid WGS 84 It is strongly recommended to use the same DEM that was used to orthorectify the reference image as DEM errors
17. ATH ii Not using a previously defined custom IDL search path definition usr local rsi idl_ 6 0 products envi_ 4 0 bin envi_ setup bash unset IDL _ PATH IDL PATH home myusername myEnviConfig lt IDL_ DEFAULT gt export IDL_ PATH 3 If you already have a save _ add directory where you usually put your sav files copy the COSI Corr module cosi_corr sav into it If you are not installing COSI Corr for the first time make sure to discard any older version that might be in this directory DO NOT change the module s name If you are adding sav files for the first time create a directory named save add at any location you want say home myusername myEnviRoutines 4 With the previous release of COSI Corr the ENVI menu text file envi men needed to be edited This step is not necessary anymore If you are installing COSI Corr for the first time the installation is complete If you have previous releases of COSI Corr installed you need to delete your own ENVI menu text file envi men in home myusername myEnviConfig 5 Edit the envi cfg file in home myusername myEnviConfig to point to its customized files You should at least specify the following path default save add directory home myusername myEnviRoutines save add Notice that this path can also be set through ENVI s GUI under File gt Preferences Default Directories Save Add Directory 10 6 The changes will be implemente
18. GCPS 3 Exterior Orientation Enter the name of the Exterior Orientation file to be created and click OK The file will contain the six EO parameters longitude degree latitude degree altitude meter w radian radian amp radian Note that is given with the North as a reference and can be seen as the sum of the aircraft azimuth and yaw The EO file is then used during the image orthorectification Sec 8 4 3 Miscellaneous When optimizing GCPS generated from tie points selection between an aerial image and a shaded DEM if the difference in resolution is large example 1 m image vs 30 m SRTM or if the topographic features are 14 S Exterior Orientation DER OK Select Interior Orientation D StudyCaseM Image 1 t t e Select GCPS File D sStudyCaseNGCPS Image 1 t t Queue Dutput Select Exterior Orientation D StudyCaseXED Image 1 txt Figure 4 Exterior Orientation tool too thin for a good optimization it is recommended to geolocalized first a satellite image with the shaded DEM and use the subsequent orthorectified satellite image as a reference 5 Satellite Imagery Specific 5 1 Ancillary File This function Satellite Imagery gt Ancillary File gt Satellite to study rearranges the ancillary data of a satellite image into a common file format that will be used afterward in COSI Corr This ancillary file will contain the positions attitudes and look directions of the satellite
19. NSEE a nonexclusive non transferable royalty free license under the copy right rights and any applicable patent rights to use COSI Corr for internal research purposes only This license specifically excludes the right to sublicense COSI Corr in any form and it also excludes the right to use COSI Corr for any commercial or for profit purpose 4 LICENSEE agrees to grant Caltech a fully paid up royalty free nonexclusive license for educational and research purposes to any Derivative Works of Software that are owned or controlled by Licensee 5 LICENSEE may incorporate Software with other source code developed by LICENSEE Incorporated Work for the sole purpose of using Software for research internal to LICENSEE and not for any other redistribution LICENSEE may not distribute any Incorporated Work outside of LICENSEE and specifically LICENSEE may not provide Software or any Incorporated Work under an open source license such as the Gnu Public License www gpl org If the creation of an Incorporated Work would require LICENSEE to distribute Software under an open source license then LICENSEE agrees not to make such incorporation 6 Software is experimental in nature and is being licensed as is The license of COSI Corr does not include any technical support or documentation 7 LICENSEE hereby represents and warrants that it is a not for profit entity 8 CIT represents and warrants that it has the right to license Software 9 LICENSEE
20. Tools gt Filter Image Values allows you to filter and change pixel values in an image based on their values The file can contain several bands Typically this function is used to filter out outliers or values with a weak SNR in a correlation file 1 Select the file and the bands of interest Non selected bands will not be changed 2 For each band selected enter the minimum maximum and replace values Fig 16 3 Select a file name if you want to save the filtered file on the disk or leave the field empty for in memory load Every pixel in the band whose value is smaller than the minimum or larger than the maximum will be assigned the replace value Note that for a pixel in a band changed pixel at the same location in the other bands selected will be changed too by their respective replace value Note This function is not internally tiled which means that it can only be used with files whose size are reasonable compared to the available dynamic memory 29 51 1 North South CorrelationSeismo D X available Bands List fx fg CorelationSeismo O East West North South o SNA a Map Info C GrayScale RGB Color C pR Notth South CorelationSeismo Gg NorhSouth CorrelationSeismo C g SNR CorelalionSeismo Dims 630 x 594 Floating Point BSQ LoadRGB Display 1 Select Image to define conection from D CorrelationSeismo Angle to rotate image to stack stripes und
21. User s Guide to COSI CORR Co registration of Optically Sensed Images and Correlation Frangois Ayoub S bastien Leprince and Lionel Keene California Institute of Technology 1200 East California Blvd Pasadena CA 91125 USA February 2 2009 Abstract This document is a user s guide for the installation and the use of COSI Corr COSI Corr is a software module integrated in ENVI which provides tools to accurately orthorectify co register and correlate optical remotely sensed images aerial and pushbroom satellite images with the ultimate objective of retrieving ground surface deformation from multi temporal images Although this module is tailored to measure ground deformations such as coseismic deformation glacier flows sand dune migrations slow landslides etc it can also be a valuable tool for many other change detection applications requiring accurate coregistration of images sub pixel detection capability is expected depending on the quality and the noise level of the data COSI Corr User s Manual February 2 2009 Copyright 2006 California Institute of Technology Contents 1 10 Preface 1 1 About This Document 1 2 Who Will Use This Document 13 About COSECorr cess l4 Support oe caa 6o Rory 9 RR LB Citation uoce cox ok c ow os ES 10 Disclaimer oaa RR a A Installation and Getting Help 2 1 How to get COSE Corr 2 2 Requirements sess 2 3 Window
22. additional bands at the end of the file The non selected bands remain unchanged Fig 19 10 3 2 Automatic Orientation 1 10 11 Image to define correction from Select the bands usually only the EW and NS bands from which the correction will be defined Ancillary file of one image Select the ancillary file of the image causing the undulations to be removed GCPS file if any Select the GCPS file if any that was used to orthorectify the image This is an optional parameters DEM file if any Select the DEM file if any that was used to orthorectify the image Attention the DEM must be valid on the entire image area This is an optional parameters Stripes undulations direction Select whether the artifacts to removed are oriented cross track or along track For example attitude undulations will cause artifacts in the cross track direction whereas a CCD artifact will cause along track stripes Image to apply the correction to if different If the corrections are meant to be applied to a file different than the one they are determined from select it accordingly It must be of the same size with the same number of bands that the file used to determine the correction A typical case is when a denoised and smoothed correlation file is used to determine the stripes correction but the correction is applied to the raw correlation file If this field is left empty the correction will be a
23. ages of good quality The statistical correlator maximizes the absolute value of the correlation coefficient and is coarser but more robust than the frequential one Its use is recommended for correlating noisy optical images that provided bad results with the frequential correlator or for correlating images of different content such as an optical image with a shaded DEM 4 Correlation File Select the name of the correlation file to be created If both images are georeferenced with the same projection and resolution the georeferencing is accounted for and only the geographic overlapping part is correlated Otherwise the correlation is pixel based 9 1 Frequential Correlator l Frequential Correlator Parameters R Window Size 128 v to for multiscale E Step 16 Robustness lteration 2 v Mask Threshold 0 90 Resampling longer process Grided Output IV Ok Cancel Figure 12 Frequential correlator parameters The parameters for the frequential correlator are Fig 12 1 Window Size Size in pixels of the sliding window that will correlate the images The size should be a power of two The frequential correlator can be used in two modes a The simple mode where a unique window size is specified Leave the minimum window size field empty to for multiscale b The multi scale mode The multi scale correlator accepts a maximum and a minimum window size Patches with the
24. agrees that any person within LICENSEE utilizing Software will be advised of and is subject to the conditions in this Agreement 10 NO WARRANTY SOFTWARE IS PROVIDED AS IS WITHOUT WARRANTY OF ANY KIND INCLUDING ANY WARRANTIES OF PERFORMANCE OR MERCHANTABILITY OR FITNESS FOR A PARTICULAR USE OR PURPOSE AS SET FORTH IN UCC 23212 2313 OR FOR ANY PURPOSE WHATSOEVER HOWEVER USED IN NO EVENT SHALL CIT BE LIABLE FOR ANY DAMAGES OR COSTS INCLUDING BUT NOT LIMITED TO INCIDENTAL OR CONSE QUENTIAL DAMAGES OF ANY KIND INCLUDING ECONOMIC DAMAGE OR INJURY TO PROPERTY AND LOST PROFITS REGARDLESS OF WHETHER CIT SHALL BE ADVISED HAVE REASON TO KNOW OR IN FACT SHALL KNOW OF THE POSSIBILITY LICENSEE BEARS ALL RISK RELATING TO QUALITY AND PERFORMANCE OF SOFTWARE OR ANY DERIVATIVE WORKS THEREOF 11 All right title and interest in and to all data information and inventions that result from use of Software by the LICENSEE shall vest in and belong to the LICENSEE 12 This Agreement is governed by the laws of the State of California and any action brought hereunder shall be within the state of California 2 Installation and Getting Help 2 1 How to get COSI Corr Users must register through the Caltech TO web site and accept the licensing agreement to download COSI Corr http www tectonics caltech edu slip history spot coseis index html A zipped package containing the COSI Corr module and the User s guide should be downloaded and installed S
25. allow to control the amount of aliasing introduced Theoretically to completely avoid aliasing the largest interdistances must be taken as the resampling distances However the matrices interdistances values may be cor rupted by some outliers due to some DEM errors missing values As a consequence matrices inter distances can be filtered out by entering the percentage of values to consider A value of 10096 will return the largest interdistance found for each X and Y dimension If the resampling distances are computed on the fly during the resampling process an automatic filter at 99 5 is set This allows to filter out distances the 0 596 larger distances are discarded corrupted by outliers and in the case of no outliers to let through only a small amount of aliasing Click OK The computed resampling distances will be printed in the IDL output window Miscellaneous A queue manager is available in COSI Corr to allow batch processing An unlimited amount of tasks can be queued and will be processed on a first selected first processed basis When selecting data for a process to be queued the data to be selected may not exist yet for example when it is supposed to be computed in a task queued before Depending on the type of data to be selected ENVI file Click on Cancel A regular file selector will be displayed Enter the name at the correct path location of the file to be created Note that in this situation spatial and s
26. and J P Avouac Co registration and Correlation of Aerial Photographs for Ground Deformation Measurements submitted 2007 Ayoub et al 2007 The main tasks performed by COSI Corr are precise orthorectification images co registration and cor relation Although the orthorectification and co registration are tailored for remotely sensed images the correlation can be applied to any types of images Along with those three main tasks several post processing utilities are available such as a a denoising tool a vector field display tool a profile stacking tool a destriping tool COSI Corr has been designed to retrieve the sub pixel displacements between optical images However it is necessary to understand that even though images will be used to their full extent the limiting factors severity uncorrected topography noise resolution will affect the measurement results 1 4 Support COSI Corr has been developed at the California Institute of Technology Caltech http www caltech edu supported by the National Science Foundation NSF http www nsf gov grants EAR 0409652 and EAR 0636097 and by the Caltech Tectonics Observatory TO http www tectonics caltech edu 1 5 Citation The Caltech Tectonics Observatory TO is making this module available to you in hopes that the software will enhance your research A number of individuals have contributed to the development of COSI Corr The authors would like to thank
27. ar to the one described in Sec 8 2 c Correlator engine Select the correlation method used to correlate the patches and retrieve the displacements to correct Usually a window size of 128 or 256 pixels is used It will allow for a good co registration on the long wavelengths The statistical correlator is advised when the reference image is the shaded DEM whereas the fequential correlator is advised when the reference image is an orthorectified image For more information on the correlator engines and their options see Sec 9 Weight GCP with correlation SNR If checked GCPS will be weighted with the correlation SNR of the previous loop This allows to give more weight on GCPS whose patches have a better correlation For the initialization GCPS will be assigned the SNR read from the GCPS file or assigned an equal SNR in case of tie points and ICP files If not checked GCPS will be constantly weighted with the SNR from the initialization a na e Dynamic display of optimization If checked a graphic window displaying the successive patches will be displayed as the optimization goes This allows for a visual check of the patches that are correlated For instance it is a convenient way to check that GCPS have not been chosen too close to the images borders 7 Optimized GCPS Select the filename of the optimized GCPS that will be created The Select All button allows you to select success
28. band name in the band list causes the parameter controls to be updated with that band s particular parameter set NOTE The user must supply a noise parameter for each band since this parameter has no default value All other parameters may be left at their default settings if so desired 5 Filtered bands file Select the name of the filtered bands output file The filtered bands are automat ically assigned the same names as the originals but in addition have NLMfiltered appended to the end of them In addition the header file will list the filter parameters for each band NOTE During processing the ENVI IDL user interface is unresponsive A progress bar is displayed that increments after each band has been filtered 26 m Non Local Means Filter Select Bands to filter C Documents and Settings Cosi Con ASTER Con Select SNR file optional Not Selected Queue Band List Filter Params Advanced H noise parameter Search area dimension 21 Patch size 5x5 Weighting method Averaging C Linear regression __ RemoveBand Restore all defaults Clear Band List Output Select Filtered bands file Not Selected Figure 14 Non Local Means Filter 10 1 2 Filter Parameters Fig 14 H noise parameter This number is used to control the degree of denoising and is proportional to the standard deviation of the noise A common value for H is between 0 5 and 2 times the standard deviation
29. cur defaulting to the standard averaging method Minimum of weights Only used if the Linear regression weighting method is selected otherwise it is ignored Minimum number of weighs above the minimum weight value threshold so that the Linear regression filtering can occur Otherwise the filtering method defaults to the averaging filtering method This condition avoids fitting the noise when only very few significant weights exist in the search area T his parameter therefore only makes sense if it is larger than three If it is too large linear regression filtering tends to occur less defaulting to the standard averaging method Center data point Indicates whether or not the center data point ie the data point being filtered is included in the weight calculation The default condition is to omit the center data point in the weighting calculation Noise parameter Indicates whether the noise parameter H is fixed at the user supplied value Otherwise an adaptive algorithm Zimmer et al 2008 is used to select the noise parameter at each filtering point This adaptive method works poorly and it is not advised to use it but it is left here for further tests and developments Weighting type Refers to the way the local weights relate to the patches similarity measurements 28 Standard Computes the patch weights according to a Gaussian distribution Buades et al 2008 Bisquare A modified form of Standard with a fi
30. d displays a vector field based on displacement maps or ASCII files Loading Data To load data in the Vector Field tool do File gt Open Two kinds of data can be entered e ENVI File When selected you will be prompted to enter the E W band and N S band successively of a displacement map to construct the vector field The E W and N S band selected and their subset must be of the same size and must be georeferenced A typical entry is a correlation file e TXT File An ASCII file which must be of the form Easting Northing DEasting DNorthing DEasting and DNorthing refer to the vector value in Easting and Northing directions at the location indicated by Easting and Northing A typical entry is a GPS measurements file Note that additional data from ENVI file or TXT file can be added to the vector field display but the ground footprint of the display will be determined by the first data entered Vector Tool Select Processing gt Tool Gui The vector field graphic options available are the following Fig 20 e Graph Title Enter the title of the vector field display e Maximum vector value Enter the maximum value of the displayed vectors Vectors of superior values won t be displayed 32 A 1 North South Memory6 E x ZI Available Bands List a m Ed Fie Overlay Enhance Tools Window ae 8 Memor o East West 9 North South o SNR o EastAWest_comection 3 Nodh South correction
31. d when you re start ENVI Before that source the cshrc tcshrc or bashrc to apply the changes to your current session 7 If the installation worked correctly the COSI Corr menu should appear in the ENVI tool bar Fig 1 It is recommended to register to and visit regularly the COSI Corr forum http www tectonics caltech edu forum where you will find tips bug reports thematic technique discussions and feedbacks from other COSI Corr users SI ENVI DER File Basic Tools GERA Classification Transform Filter Spectral Map Vector Topographic Radar Window Help Aerial Imagery Satellite Imagery gt Tied Points GCPS gt Correlation Tools About Cosi Corr Figure 1 Example of the COSI Corr menu inserted in ENVI between the Basic Tool and Classification top level menus 2 5 Getting Help As a courtesy we will try to provide assistance To ask for information help report a bug or a suggestion please first browse the COSI Corr forum http www tectonics caltech edu forum as the problem you are facing may have been already reported If you do not find an answer do not hesitate to post your questions comments on the forum To contact the COSI Corr team directly you can also send an email to cosicorr help gps caltech edu The software module was released for the first time in 2006 and may still contain bugs and errors as it is usually the case with new softwares We apologize in advance for the inconvenience and ask
32. e correction assumes a standard atmosphere and follows an adapted method described in Wolf amp Dewitt 2000 Once the parameters entered select a name for the IO file to be created and click OK Note 1 The radial and tangential lenses distortions as well as the atmospheric diffraction have typically an amplitude of around 1 to 4 um only Due to the scanners resolution and stability consequences will not be dramatic if they are not accounted for Note 2 If the calibration report is not available the IO can still be built but the lenses distortions principal point offset and fiducial points measures will not be accounted for The scanning resolution and the fiducial points coordinates in pixel are needed and the principal point is assumed to be at the crossing of the lines joining the opposite fiducial points 4 2 Exterior Orientation This function Aerial Imagery gt Exterior Orientation computes the Exterior Orientation EO of the camera Fig 4 It describes the position and the angular orientation of the camera in the ground coordinates system at the time of exposure It is composed of the spatial position which corresponds to the camera optical center coordinates i e Easting Northing Altitude and the angular orientation which is composed of three 13 m Interior Orientation Camera Calibration No Camera Calibration Input Focal Length meter 0 153715 Principal Point x mm 0 002 y mm 10 004
33. e rotated to align vertically the stripes Enter the rotation angle degree necessary to align the stripes vertically Tip the ENVI rotate tool Basics Tools gt Rotate Flip Data can be used first to determine precisely the angle 3 Image to apply the correction to if different If the corrections are meant to be applied to a file different than the one they are determined from select it accordingly It must be of the same size with the same number of bands that the file used to determine the correction A typical case is when a denoised and smoothed correlation file is used to determine the stripes correction but the correction 30 is applied to the raw correlation file If this field is left empty the correction will be applied to the file from which the correction is determined Corrected File Select the filename to create if you want to save it to the disk Otherwise leave the field empty for in memory computation but keep in mind the size of the image in regards to the available dynamic memory Click OK After a short computing time a rotated image with the undulations aligned vertically will be loaded in memory Select the file and select the spatial subset that will be stacked to determine the correction Fig 18 The same spatial subset will be stacked on each selected band Click OK The output image will be the original file with the selected band corrected The correction applied to the bands is appended as
34. eater or equal to the window size then all measurements will be independent 3 Robustness Iteration Number of times per measurement the frequency mask should be adaptively re computed The mask contributes in reducing the noise on the measurements 2 to 4 iterations is satisfying in most cases Leprince et al 2007 4 Mask Threshold Allows the masking of the frequencies according to the amplitude of the log cross spectrum A value close to unity is appropriate in most cases See Leprince et al 2007 for more details 5 Resampling Patches to correlate are relocated from sinc resampling This option theoretically elim inates most of the biases at the sub pixel scale If used the processing time is greatly increased on average by a factor of 10 However on noisy images its usefulness has been noticed only on a very few occasions 6 Grided Output Check this option if you want to obtain a displacement map that can be superimposed with other displacements maps of the same are or that can be mosaiced exactly 9 2 Statistical Correlator I Statistical Window Size Step s Search Range Grided Output v _0K Cancel Figure 13 Statistic correlator parameters The parameters for the statistical correlator are Fig 13 1 Window Size Size in pixels of the patches that will be correlated 2 Step This parameter determines the step in pixels between two sliding windows If
35. ec 2 3 2 4 All materials obtained are subject to the licensing agreement 2 2 Requirements COSI Corr has been developed in Interactive Data Language IDL http www ittvis com idl and has been integrated in ENVI http www ittvis com envi Users must therefore have ENVI release 4 0 or newer installed IDL and ENVI are platform s independent and COSI Corr has been tested under Windows 2000 XP Vista and also under Unix Linux and Mac OS systems Due to the usually large size of remotely sensed images it is highly recommended to increase ENVI Cache size and Image Tile size to around 200Mb and 40Mb respectively ENVI gt File gt Preferences gt Miscellaneous if the computer hardware allows it Lack of memory and unable to allocate errors are usually due to a too small Cache size and Image Tile size 2 3 1 2 2 4 Windows Installation Unzip the downloaded file Move the COSI Corr module cosi_corr sav to the ENVI save add directory DO NOT change the module s name This file contains all the compiled source code of the COSI Corr module The ENVI save add directory path depends on the location of IDL ENVI on your computer and it may look like this for an installation at the root C RSI IDL60 products envi 0 save_ add or C Program Files ITT IDL70 products envi 5 save_ add for versions 4 4 and after If you are not installing COSI Corr for the first time make sure to discard any older version t
36. er quality but faster processing e Kernel Weighting The theoretical Sinc kernel has an infinite length Due to the kernel trunca tion some ringing effect due to the Gibbs phenomenon are introduced in the reconstructed image 22 l Sinc Kernel Parameters R Kernel Size pix 25 Kemel Weighting v Resampling Distances Dist Dist Y NB Leave empty for pre resampling computation Subset resampling distances area computation No C Yes Figure 10 Sinc kernel parameters If checked kernel edges are tapered down to remove the truncation discontinuities Please note that the weighting performed will not be appropriate if you choose a kernel size larger than 25 e Resampling Distances They define the kernel lobes size in pixels and are defined from the mapping matrices Leprince et al 2007 If left empty they are computed on the footprint of the image only and are filtered at 99 5 to discard outliers if any Subset resampling distance area This option allows you to select a subset on the matrices on which to compute the resampling distances If selected the subset is defined geographically through the spatial selection of a georeferenced file Usually the area is defined from the DEM as corrupted resampling distances areas come from error gap outlier non coverage in the DEM Note The tool Tools gt Matrices Interdistances can be used to compute and check the resampling dista
37. hat might be in this directory With the previous release of COSI Corr the ENVI menu text file envi men needed to be edited This step is not necessary anymore If you are installing COSI Corr for the first time the installation is complete If you have previous releases of COSI Corr installed you need to edit the ENVI menu text file envi men located in the ENVI menu folder whose path might be C RSI IDL60 products envif 0 menu or C Program Files ITT IDL70 products envi45 menu for versions 4 4 and after and remove the COSI Corr menu Save and close the file Start ENVI If the installation worked correctly the COSI Corr menu should appear in the ENVI tool bar Fig 1 It is recommended to register to and visit regularly the COSI Corr forum where you will find tips bug reports thematic technique discussions and feedbacks from other COSI Corr users http www tectonics caltech edu forum Users planning to operate the Non Local Means Filter Sec 10 1 also need to a Make sure they satisfy the following requirements e 32 bit or higher Microsoft Windows M e Intel Pentium 4 or higher CPU e IDL6 3 ENVIA 3 or higher b Copy NLMeansFilterDll def NLMeansFilterDIl dlI NLMeansFilterDll dlm into CARSINIDL60N binNbin z86 or C Program Files T INIDL TON binNbin x86 for versions 4 4 and later This file path may be slightly different depending on your versions of ENVI IDL c Download
38. he fault Once the fault is mapped save the ROI using File gt Output ROIs to ASCII 2 Take note of the fault origin pixel coordinates using the Cursor Location Value tool as it will be needed for the fault orientation 33 Vector Tool Chi Chi Di Cet erie Graph Options Graph Title Chi Chi Displacement Fie Maximum Vector Value 20 Ratio Arrow Length 0 08D 2 680X 108 Unit Meter Axis Color Black y Background Color White v Vector Field Options SPOT Measures GPS Measures o SS NSNS SL E RR X 2 670x108 TAS ne M S L TRESS LUNNNNN SN eS AROS ISSN ENS NNN ALAS ao SERRARA a tt AS Vector Field Name GPS Measures Average Window Size hm Anti 2 660x108 Step Vector Color Red S Line Thickness 3 IN MM een d Toa efte Ke TAA o arcu Se a ASK RS M rrr IeVTtTS 5 2 85x105 2 70x105 2 75x105 2 80x105 NI kann nni hr kero A A C VV MR mL Beer nnt nti Pron ee ee T NN Pee RN ASRS gt Dr x ts o a x 0 5 1015 20 25 30 Meter Figure 20 Vector field tool Displacement field of the 1999 Taiwan Chichi earthquake form a pair of SPOT images 10 5 1 Orient Fault This step Tools gt Stacking gt Orient Fault will rearrange the data contained in the fault profile file retrieved from the ROI tool This process is necessary for two reasons First reason practical is
39. here you do not have write permission Following is an example of lines to add expecting previously defined IDL search path variable definition source usr local rsi idl_ 6 0 products envi 4 0 bin envi setup setenv IDL_ PATH home myusername myEnviConfig IDL_ PATH You will need to change the home directory path shown above as home myusername myEnviConfig to your own home directory path You may also need to change the directory path to the envi setup file if your ENVI installation is in a location other than usr local rsi If you anticipate that IDL_ PATH will be undefined no prior IDL search path customizations then be sure to use the string lt IDL_DEFAULT gt in place of IDL_PATH at the end of the second command Notice in the following example that lt IDL_DEFAULT gt is inside the right single quote character source usr local rsi idl 6 0 products envi 4 0 bin envi setup unsetenv IDL_ PATH setenv IDL_ PATH home myusername myEnviConfig lt IDL_ DEFAULT BASH Shell Set up environment for ENVI 4 0 and above and modify IDL search path variable IDL Path Your ENVI installation also contains a setup file for the Bash shell Place the following equivalent commands in the bashrc file in your home directory HS C i Using a previously defined IDL search path definition usr local rsi idl 6 0 products envi_ 4 0 bin envi setup bash IDL PATH home myusername myEnviConfig IDL_ PATH export IDL_ P
40. ial or GCPS file satellite 20 l Orthorectification Resampling M Orthorectification Y Resampling OK Orthorectification Resampling Cancel Input Queue Select 10 File Di StudyCaseMO Image_1 txt Select EO or GCPS File D StudyCase GCPS_Image_1 tst Select DEM optional D NStudyCaseXDEM Map Grid From Raw Image From Georeferenced Image Manual Edit Projection UTM WGS 84 Zone 11 North Grid Coordinates Upper Left E w 543324 00 N S 3806072 0 Lower Right E w 554552 00 N 5 3735208 0 Resolution E w 1 0000000 N S 1 0000000 Output Select Mapping Matrices D StudyCase Matrice_Image_1 mat Figure 8 Orthorectification tool e Aerial image Select the EO file or the GCPS file In case of GCPS file the EO will be computed prior to the matrices computation e Satellite image Select the GCPS file If not selected the orthorectification will only use the ancillary data file to orthorectify the image The accuracy will therefore depends on the satellite ancillary data accuracy 3 DEM Select the DEM file to account for the topography The file must have a valid map information and can be in any projection If not entered the orthorectification will take place assuming a flat topography at altitude 0 above the ellipsoid WGS 84 4 Map Grid Define the ground grid on which the image will be projected Currently only the UTM projection is supported The hemisphere North or South the UTM zone 1 t
41. ighting metrics for enhanced denoising e Ability to account for the presence of missing values NaN present within the input data set 10 1 1 Filter Process The non local means algorithm filters data by stepping through the data set one value at a time At each data point a small region of surrounding values typically 5x5 or 7x7 is compared with other non local regions patches of the same size A larger region around the central patch is used as the search area The filtered value is computed as an average of the values within the search area weighted by their measure of similarity with the patch centered at the pixel to be filtered This approach has the effect of preserving true signals and features 1 See 2 3 for filter installation available only under Microsoft Windows platforms 2 Bands to filter Load one or more bands to be filtered Fig 14 3 SNR file optional A band weighting signal to noise ratio can be selected and applied during filtering The SNR file must have the same spatial size as the bands to be filtered should be floating point values comprised between 0 0 and 1 0 and will be applied to all bands selected 4 Upon loading the bands have been automatically assigned default filter parameters see 10 1 2 10 1 3 for parameters details Each band is associated with its own set of filter parameters and can therefore be processed with a set of data specific parameters if the user wishes Clicking on a
42. ively all the files necessary Besides the optimized GCPS the output file will also contain a record of the files and parameters used as well as information on the optimization The average and standard deviation of the mis registrations in each North South and East West component are recorded at each iteration This allows to check the convergence of the process and the quality of the GCPS generated A residual misregistration as small as possible is desired Note that if the GCPS were optimized with a Tie Points file the x and y pixel coordinates of the optimized GCPS are minus 1 compared to the initial coordinates COSI Corr is using a pixel coordinates system originating at 0 0 unlike ENVI which starts at 1 1 8 Orthorectification and Resampling This function will orthorectify an image Aerial Imagery or Satellite Imagery gt Orthorectification Resampling It is composed of two steps The pixel mapping between the raw image and the futur orthorectified image and the resampling of the image according to the mapping Usually those two steps are processed together one after the other If you want to process only one of the two uncheck the unwanted task 8 1 Orthorectification This step constructs the mapping matrices between the raw and the orthorectified image Fig 8 1 Ancillary data file satellite or IO file aerial Select the data file corresponding to the image to orthorectify 2 EO or GCPS file aer
43. lable for the SPOT 2 HRV 1 and SPOT 4 HRV 1 instruments QUICKBIRD Imagery The level 1B Basic is required Panchromatic and multi spectral images can be processed Note that only full scenes not fractional are accepted The files eph att geo and imd will be needed and must be located in the same folder only one of these 4 files need to be entered in the auxiliary file field the other ones being retrieved automatically 15 WORLDVIEW 1 Imagery The level 1B Basic is required Note that only full scenes not fractional are accepted The files eph att geo and imd or the xml will be needed and must be located in the same folder only one of these 4 files need to be entered in the auxiliary file field the other ones being retrieved automatically 6 Tie Points and GCPS 6 1 Tie points Selection The tie points selection consists of pairing similar points between two images It will most of the time consists in associating points between a georeferenced image and a non georeferenced image typically between an orthorectified image and a raw image It allows to associate a ground coordinates to a point in a raw image 1 Open the two images for the tie points selection 2 Select the Tie Points GCP gt Select Tie Points Image to Image tool Base Image refers to the georeferenced image master and Wrap Image refers to the raw image slave 3 Select tie points between images See ENVI Help for
44. largest window size are correlated first and if the correlation succeeds it is re executed on patches with decreased size power of two and accounting for the displacement previously found The process is iterated until the minimum window size is reached or until the correlation fails In this last case the measurement found from the previous larger size is kept and the process moves on to the next patches The multi scale correlator is mostly useful under two situations 24 e When the displacements to estimate are greater than half the window size In that situation the correlator cannot determine the displacements Use the mutli scale correlator to set up a large window size which will be larger than two times the expected displacement and a small size to the minimum acceptable window size in term of noise e When the noise in the image is not uniformly distributed Using the multi scale correlator will allow to retrieve displacement in noisy areas with large windows and still use small windows in less noisy areas It is customary to select the smallest window size that will provide a reasonable amount of noise from experiment a window size of 32x32 pixels is the minimum and with good quality images a window size of 32x32 or 64x64 usually yields good results as it will increase the density of totally independent measurements 2 Step This parameter determines the step in pixels between two sliding windows If the step is gr
45. late windows centered on each point the optimization window size should be kept in mind when picking tie points e Pay attention to the points surrounding Are features recognizable between the two images Iry to select points whose neighborhood contain easily identifiable features or patterns Are there any tem poral decorrelations man made changes shadowing differences Prefer areas of low topography to minimize uncorrected stereoscopic artifact e It is not necessary to select tie points precisely as the optimization will correct them With the frequential correlator the maximum placement error allowed on the initial GCPS will correspond to half the correlation window size With the statistical correlator a search range will have to be defined If you select more than 3 points the tie point selection tool provides you with a RMSE on a linear fit This RMSE is a good approximation of the average error on the tie points Later in the statistical optimization the search range can be set between 1 5 2 times this RMSE 16 6 2 Tie points to GCPS 7l Convert Tied Points to GCPS ex x Select Tied Points File D StudyCase tpts_Raw_Img2_with_Ortho_Ima1 pts Em Select Reference Image D AStudyCase Ortho_Image_1 mar Select DEM File optional D NStudyCase DEM Select Offset Field optional D StudyCase E xternal Displacement Map Output Select GCPS File D StudyCase GCPS_Image_2 txt Figure 5 Tie points
46. more details on this function 4 When done save your tie points selection using File gt Save GCPs to ASCII and not Save Coefficient to ASCII The file created will be a list of the form x master y master x slave y slave in pixel Note 1 This is an ENVI function that can also be found in Map gt Registration The ENVI tool accounts for the xstart and ystart contained in the image header Make sure they are set to 1 as COSI Corr assumes so Most likely this will not be the case if your georeferenced master image is a subset of a larger image that has been cropped using ENVI Editing the header of your master image and forcing the xstart and ystart to 1 will not corrupt your data and is mandatory Note 2 If tie points are selected between an orthorectified image and a raw image to be converted to GCPS and optimized here are some guidelines to pick them adequately e At least three points must be selected If the wrap image is to be co registered with a shaded DEM a larger number of points 15 to 30 if possible should be selected to average the probable correlation errors due to the difference in images content e Spread the points as much as you can in the image but select them away from the area where ground displacement is expected If displacement is expected in the whole image select points in areas of smallest displacements e Do not select points too close to the images borders As the optimization will corre
47. nces Sec 10 6 before resampling 4 Resampled Image Select the name of the resampled image that is going to be reconstructed from Image according to the Mapping Matrices 9 Correlation and Displacement Measurements l Correlation On OK Select Pre Earthquake Image D StudyCase Ortho_Image_1 Cd Select Post Earthquake Image D NStudyCaseNOrtho Image 2 Queue Correlator Engine Frequential Options Output Select Correlation File D StudyCase Displacement_Map Figure 11 Correlation parameters selection tool 23 This function Correlation correlates two images and provides a map of the relative displacements Fig 11 1 Pre event Image Select the first image of the pair This image is considered the reference 2 Post event Image Select the second image of the pair The correlation result provides a displacement field using the convention eastward and northward positive This displacement field is the horizontal ground displacement that should be added to the pre event image to retrieve the post event image 3 Correlator engine Select the correlator engine Currently two correlators are available frequential Sec 9 1 and statistical Sec 9 2 The frequential correlator is Fourier based and is more accurate than the statistical one It should be use in priority when correlating optical images However this correlator is more sensitive to noise and is therefore recommended for optical im
48. nite taper and steeper fall off Goossens et al 2008 Modified Bisquare A modified form of Bisquare but with even steeper taper and fall off Goossens et al 2008 The Standard i e Gaussian and the Bisquare methods have proven to be the most useful in our tests Note that for a given noise level in an image a particular value of H has to be selected for each method NOTE The denoising results provided by the filter using the default parameters may not be appropriate for a given data set In these cases the results will be sub optimum and it becomes necessary to modify the optional parameters so as to achieve optimum denoising Any combination of parameters is possible with the following two exceptions Minimum weight value and Minimum of weights These two parameters only take effect if the user has selected Linear as the weighting method Otherwise they are ignored and changing their values will not affect the results To speed up parameters adjustment during trials and errors note that a spatial subset of the image to be filtered can be selected Then the filter is only applied on this image subset 10 2 Discard Replace Image Values l Values to filter North South Min value empty for no limit North South Max value empty for no limit Replace filtered values by empty for NaN Ok Cancel Figure 16 Band parameters selection tool for image filtering This tool
49. o 63 the top left and bottom right grid corners coordinates and the ground resolution must be defined during this step Three options are available to define the grid e From Raw image Select the spatial subset in the raw image to define the ground grid onto which orthorectify the image e From Georeferenced image Select an existing georeferenced image to define the grid The georeferenced image must be in UTM projection The UTM zone hemisphere and resolution will be retrieved from the image map information The top left and bottom right coordinates will be retrieved from the spatial subset This option is useful when orthorectifying the second image of a pair as it retrieves the grid information of the first orthorectified image e Manual Edit Select modify manually the grid The From Raw Image option proposes the UTM zone in which the top left corner of the image is lying If the image is between two UTM zones and that this automatic selection is not adequate the Manual Edit is required 21 Note Inthe Grid Parameters window the button Adjust grid to be multiple of resolution forces the grid corners to be multiple of the ground resolution selected This action should always be performed to make sure that all orthorectified images are later compared from the same grid i e within the same reference frame 5 Mapping Matrices Select the name of the matrices file to create The name when entered i
50. of the noise and it depends on the other parameters selected The stronger dependencies are on the weighting type Standard Bisquare or Modified Bisquare and on whether the center data point is omitted or not in the advanced parameters With the default parameters a value of H close to 1 6 times the noise estimated standard deviation is a good estimate This parameter does not have a default value Therefore the user MUST supply a noise parameter for each band prior to running the filter The noise standard deviation can be estimated from the image local statistics observed over areas with presumably constant values The ENVI ROI tools can be conveniently used to this end Search area dimension This number refers to the dimensions of the search area around each data point Since the shape of the area is fixed as a square the user need only supply one value indicating the dimension of the side For example if the user enters 17 this instructs the application to use a search area of size 17 x 17 pixels The default value is 21 corresponding to a search area of 21 x 21 data points This value must be an integer smaller than the smallest data set dimension CAUTION Large search areas will cause the application to be unresponsive for long periods of time In general areas sizes from 21 x 21 to 41 x 41 pixels produce good results at acceptable execution times Patch size This selection refers to the dimension of the square patch used to
51. p tif La ES Fiduciaix 103 3460 Image 994 50 AAA AE Fiducial Y 103 3380 Image Y 818 00 lumber of Selected Points 1 Show List RMS Error N A Delete Last Point gt Review Comment gt Secure 4 sign Advanced Edting E HowTo VII Principal Points and Fiducial Coordinates i 2 180 Positions of all points are referenced to the principal point of autocollimation PPA as origin The diagram indicates the orientation of the reference points when the camera is viewed from the back or a contact positive with the emulsion up The data strip is to the left X coordinate Y coordinate A 1 Scroll 0 02203 0 000 mm 0 003 mm Indicated principal point midside fiducials 0 001 0 002 Principal point of autocollimation 0 0 0 0 Calibrated principal point point of symmetry 0 002 0 004 Fiducial Marks 103 946 mm 103 938 mm 103 944 103 941 103 938 103 954 103 929 103 938 113 002 0 013 112 991 0 008 0 010 112 990 0 012 112 993 OIA EUN 8 49x 11 03 in O Figure 2 Fiducial points selection with the help of the calibration report 5 Tangential lenses distortions correction coefficients Currently only the coefficients can be entered if supplied by the calibration report The correction applied is the one described in Wolf amp Dewitt 2000 6 Atmospheric correction Check if you want to correct for atmospheric diffraction Th
52. pectral 36 subsetting are not possible If no regular file selector is displayed the file must then exist at the current time Other Enter the name at the correct path location of the file to be created e Do not open more than one COSI Corr window at a time except for the queue manager window as crash will occur otherwise In case of an ENVI blocking crash due to more that one COSI Corr window opened bug enter in the IDL command line retall and press enter It will most of the time unblock ENVI If not you may have to restart ENVI e COSI Corr has been designed to be accurate in its computation and processes can therefore be long especially the orthorectification and the correlation Examples of processing times are given in Table 11 Processes were computed on a Pentium 4 Xeon 3 2 GHz 2Gb RAM PC using Windows XP Pro and ENVI 4 0 ENVI Cache and tile size were set to 250Mb and 40Mb respectively 37 Task Process Timing SPOT 5 Ortho Resampling 5 m 14300 x 14400 pixels grid 7h0mn SPOT 4 Ortho Resampling 10 m 7200 x 6900 pixels grid 1h 58 mn Correlation 11200 x 10800 pixels images 698 x 675 measures 36mn WinSz 32 Step 16 Mask 0 9 NbRoblter 2 No resamp Correlation 11200 x 10800 pixels images 698 x 675 measures 2h 19mn WinSz 64 Step 16 Mask 0 9 NbRoblter 2 No resamp Table 1 Processes computed on a Pentium 4 Xeon 3 2 GHz 2Gb RAM PC using Windows XP Pro and ENVI 4 0
53. pplied to the file from which the correction is determined Corrected File Select the filename to create if you want to save it to the disk Otherwise leave the field empty for in memory computation but keep in mind the size of the image in regards to the available dynamic memory Click OK After a short computing time a transformed image with the undulations aligned either horizontally or vertically will be loaded in memory Select the file and select the spatial subset that will be stacked to determine the correction The same spatial subset will be stacked on each selected band Click OK The output image will be the original file with the selected band corrected The correction applied to the bands is appended as additional bands at the end of the file The non selected bands remain unchanged 31 B Select subset to stack vertically in rotated image E E Available Bands List Sel File Optio Select Input File File Information E 1 Memory13 CorrelationSeismo 5 Select Spatial Subset File Memory13 Dims 694 x 721 Floating Point Samples il To 694 Ns 694 Lines 1 Tofa NL 721 Full Size 2 001 496 bytes Subset Size 2 001 496 bytes Subset by Image Map File AU crol Subset by Image Input Band Reset Previous OK Cancel Samples 510 lt Lines 88 OK Canes Figure 18 Destripping tool stacking area definition 10 4 Vector Field This tool Tools gt Vector Fiel
54. s Installation 2 44 Unix Installation co ee Se ee a 25 Getting Help us Rem Introduction A Typical Processing Chain Aerial Imagery Specific 4 1 Interior Orientation 4 2 Exterior Orientation 4 3 Miscellaneous Satellite Imagery Specific 5 1 Ancillary File 5 2 Miscellaneous Tie Points and GCPS 6 1 Tie points Selection 6 2 Tie points to GCPS GCPS Optimization Orthorectification and Resampling 8 1 Orthorectification s sxa sassari tdi 82 Resamplibg i a aar paa dia Correlation and Displacement Measurements 9 1 Frequential Correlator 9 2 Statistical Correlator gt Tools 10 1 Non Local Means Filter 10 1 1 Filter Process 10 1 2 Filter Parameters Fig 14 10 1 3 Advanced Filter Parameters Fig 15 10 2 Discard Replace Image Values 10 3 Destripe Image 10 3 1 Manual Orientation 10 3 2 Automatic Orientation 10 4 Vector Field 0 ae tok RE a 10 5 Stacking Profiles 22229 RT REG 10 5 1 Orient Fault 105 2 Stack nuu 10 6 Matrices Interdistances 11 Miscellaneous List of Figures DAD HW e 10 DI 12 13 14 15 16 i 18 19 20 21 22 COS Cor inte ENVI uou a o4 Roh Ro S E D eR v x X s ERR ERS oe vows 11 Aerial image fiducial points selection ee ee 13 Interior Orientation Window occ cas Ra RR 14 Ex
55. s directly reported to the matrices file name in the resampling GUI 8 2 Resampling i Orthorectification Resampling DER M Orthorectification V Resampling Orthorectification Resampling Input Select Image Di StudyCase Raw_Image_1 Select Mapping Matrices D StudyCase Matrice_Image_1 mat Resampling Kernel Since v Options Dutput Select Resampled Image D StudyCaseNOrtho Image 1 Figure 9 Resampling parameters selection tool The resampling reconstructs the image according to the mapping matrices defined previously Fig 9 l Zi Image Select the raw image to resample Mapping Matrices Select the mapping matrices file name that were defined during the orthorectifi cation If the matrices are to be computed the matrices name is directly completed when entering the orthorectification parameters Options Three resampling kernels are available Bilinear Bicubic and Sinus Cardinal Sinc The bilinear and bicubic kernel do not accept any parameters and are much faster than the Sinc The Sinc however accepts parameters and is more precise than the two other kernels It is recommended to use the Sinc kernel for an improved resampling quality and ultimate correlation The available Sinc kernel options are the following Fig 10 e Kernel Size Number of zero crossings 1 of the Sinc kernel A size odd between 11 and 25 is usually sufficient Smaller sizes can be used for coars
56. s of the 2008 International Workshop on Local and Non Local Approximation in Image Processing Lausanne Switzerland 2008 38
57. terior Orientation Window 22 222224 RR uE L3 9 373 33 3oRoR es 15 Tie Points to GCPS Window 222229 AA ee a 17 GPS text Pile Format 22333199 RAO AAA e ee wi we Re Oe 18 GUPS Optimization Window oia cias GER ee a lve ea eee ee dA 19 Orthorectification Window o i i 65454 aa aa a a a a 21 Reserpine VV MIAO ADT 22 Sine Berne Window o RUE Robo 6 a arie we wu A 23 Correlation Window os e ouod eod ho ae XO UR ERO SOR n ACA E S is e a d 23 Frequential Correlator Window eh 24 Statistic Comelabor WIBOON Lm Eu a op aoa eaaa mee cm m EO go GO A ee dece US um od 25 Non Local Means Filter gt e sacc 2444442524444 oomen m Roof 9o 9 RR A oa S S es 27 Non Local Means Filter Advanced Parameters ee e 28 Image Filter Window acu a e oo oo x RUE ee E ies ea ee ee dU E s 29 Destripping Selection Window LL 30 Destripping Stacking Window ci a ci dos aa Fee mr m SE Ye a BOR ed ad 32 Destripping Corrected Window es 33 Vector Field Window 34 Protile Stacking Wifdow 4 29939 X RR E ER RR Y 3 3 3 ROS aee eed 35 Matrices Interdistances Window 2 2 2 2 2 2 22 2 2 222 27 36 List of Tables 1 Proessses Timing Example a s acsm sidad POPs A r a a ded 38 1 Preface 1 1 About This Document The section 1 presents some general information about COSI Corr The section 2 presents the COSI Corr downloading instructions and installation guidelines Section 3 presents the successive steps necessar
58. the step is greater or equal to the window size then all measurements will be totally independent 3 Search Range maximum distance in pixels where the displacements to measure are to be searched 25 4 Grided Output Check this option if you want to obtain a displacement map that can be superimposed with other displacements maps of the same are or that can be mosaiced exactly 10 Tools 10 1 Non Local Means Filter This tool Tools gt Non Local Means Filter is an implementation of the Non Local Means algorithm for denoising datasets and images This algorithm Buades et al 2008 and its derivatives Buades et al 2006 Goossens et al 2008 Zimmer et al 2008 have demonstrated an exceptional ability to preserve fine detail while reducing additive white Gaussian noise The most common application of the non local means algorithm is to the restoration of digital images The implementation provided here extends the method to denoising of scientific data sets in general A number of modifications to the original filter have been introduced in the literature We have chosen to implement modifications proposed in Buades et al 2006 Goossens et al 2008 Major features of our implementation include e Highly optimized native code that transparently and automatically exploits parallelism and media extension instructions for rapid processing of data sets SIMD instruction set e Optional use of signal to noise we
59. thquake image a Select tie points between the post earthquake image and the orthorectified pre earthquake image Sec 6 1 b Convert these tie points into GCPS Sec 6 2 c Optimize the GCPS of the post earthquake image in order to precisely co register the post earthquake image to the orthorectified pre earthquake image Sec 7 d Compute the mapping matrices to transform the raw post earthquake image into an orthorectified image and resample it Sec 8 4 Correlate the two co registered and orthorectified images The result will be a at least three bands file containing the E W displacement map positive toward the East the N S displacement map positive toward the North and the SNR assessing the quality of the measure Sec 9 4 Aerial Imagery Specific Film based aerial images must be scanned with a high spatial and radiometric resolution to accurately retrieve the film s information A radiometric resolution of at least 8 bits 10 12 recommended a geometric resolution of 5 to 15 ym 5000 dpi to 1700 dpi and a stability of around 2 3 um are desired Zeiss and Leica for example provide suitable aerial images scanners It is recommended to scan in grayscale B amp W the negative and not the photo paper print 4 1 Interior Orientation The Interior Orientation IO of the camera gives a mathematical representation of the camera geometry and distortions This step is accomplished with the help of the camera calibra
60. tion report which is normally obtained on demand and follows the classical photogrammetry techniques Wolf amp Dewitt 2000 The Aerial Imagery gt Interior Orientation gt Fiducial Points Selection Tool function allows to select the fiducial points on the image and to enter their measurements which are read from the calibration report Fig 2 Once the points are selected save the file File gt Save Points to ASCII Users of ENVI 4 3 and newer versions will access the fiducial point selection tools through Select Fiducials in Display The Aerial Imagery gt Interior Orientation gt Interior Orientation Setup function generates the Interior Orientation file and gathers the camera information read from the calibration report Fig 3 1 Calibrated focal length in meters 2 Principal point offset in millimeters 3 Fiducial measures You can enter the points either manually or by loading the file created with the Fiducial Points Selection Tool The 2D affine transformation between the image reference system and the camera reference system will be automatically computed 4 Radial lenses distortions correction coefficients Depending on the data supplied by the calibration report enter directly the coefficients or compute them from laboratory measurements using the Radial Measures button 12 El Ortho Build Interior Orientation NOR File Options Help 21 1 Gray Scale R NAPP1790_161 dsu
61. ulations vertically degree 80 1 Select Image to apply correction to if different Not Selected Output Select Corrected File leave empty for in memory Not Selected Figure 17 Destripping tool selection 10 3 Destripe Image This tool Tools gt Destripe Image allows you to remove parallel stripes and undulations in an image A typical use for this tool is the removal of undulation artifacts in a correlation image due for example to an uncorrected attitude like an oscillating pitch or a CCD array artifact in ASTER or SPOT images The main idea is to average the artifact by stacking and subtracting the average to the image Two functions are available and are described below The Manual Orientation allows to destripe any image but the user need to supply manually the rotation angle necessary to align vertically the undu lations stripes to remove The Automatic Orientation defines automatically the affine transformation necessary to align the undulations stripes before performing the stack The transformation is defined from the ancillary file and GCPS file optional of the image responsible for the undulations stripes 10 3 1 Manual Orientation 1 Image to define correction from Select the bands usually only the EW and NS bands from which the correction will be defined Fig 17 2 Angle to rotate image The stripes stacking is operated vertically If the stripes are not vertical the image must b
62. ware is made available to LICENSEE on the following terms 1 Definitions a The Software is defined as the package consisting of the source code and the compiled version of the software that allows for Co registration of Optically Sensed Images and Correlation based on the algorithms described in S Leprince S Barbot F Ayoub and J P Avouac Automatic and Precise Ortho rectification Coregistration and Subpixel Correlation of Satellite Images Ap plication to Ground Deformation Measurements IEEE Transactions on Geoscience and Remote Sensing vol 45 no 6 pp 1529 1558 2007 and in F Ayoub S Leprince and J P Avouac Co registration and Correlation of Aerial Photographs for Ground Deformation Measurements Submitted 2007 Source Code is defined as code written in human readable format or in a high level program language c ei c Derivative Works means any work consisting of revisions annotations elaborations or other modifications to Software which as a whole represent an original work of authorship Derivative Works includes any updates and new releases of the Software developed during the term of this license inclusive of backups updates or merged copies permitted hereunder including the file structures programming instructions user interfaces and screen formats and sequences 2 CIT retains ownership of any copyright rights to the Software licensed under this Agreement 3 CIT agrees to grant LICE
63. while acquiring the image and other information such as the number of lines and columns nominal ground resolution and solar azimuth and elevation 5 2 Miscellaneous ASTER Imagery The level L1A is required For ENVI 4 1 or prior versions a pre processing of the radiance correction will be necessary and can be done with the adequate ENVI tool ENVI Basic Tools Preprocessing Calibration utilities Aster Radiance This pre processing is automatically done when opening the images in ENVI 4 2 and later versions The ASTER hdf file is expected as input Although any band can be selected VNIR SWIR TIR it is recommended to use the band VNIR 3N nadir viewing for surface deformation detection FORMOSAT 2 Imagery The level 1A is required Panchromatic and multi spectral images can be processed The METADATA dim file is needed SPOT SPOTS Imagery The level 1A is required SPOT images must be opened in ENVI using File gt Open External File gt SPOT gt SPOT for SPOT 1 4 satellites in the leader CEOS format or DIMAP for SPOT 5 or SPOT 1 4 images in the dimap format Panchromatic and multi spectral images can be processed and Leader SPOT1 4 lead dat file and Dimap SPOT5 and recently SPOT1 4 metadata dim file format are accepted Panchromatic with CCD correction accounts for the slight misalignment of the CCD arrays in SPOT1 4 The correction is established empirically for each satellite and is currently only avai
64. y for no limit Distances returned 100 000 Figure 22 Matrices Interdistances tool 10 6 Matrices Interdistances The matrices interdistances tool tools gt Matrices Interdistances computes the resampling distances Leprince et al 2007 which provide the width of the Sinc lobes in the x and y directions and represent the maximum absolute difference between adjacent pixel values in the mapping matrices They can be seen as the maximum ratio between the ortho rectified image resolution and raw image nominal resolution For example if a 5 m image is to be ortho rectified onto a 10 m grid a ratio around 2 is expected If the ratio found is outrageously large ie larger than the nominal ratio 1 3 in our example this most likely traduces an ortho rectification problem such as unphysical values in the DEM file Make sure that the DEM does not contain missing values encoded as 32767 for example All DEM elevations should be within a physical range and interpolated values should be preferred over missing values 1 2 3 11 Matrices Select the matrices file of interest Area of interest in image 1A By default the resampling distances will be computed on the whole matrices This button will allow you to select the image 1A subset onto which compute the resampling distances The subset can also be selected manually Distances returned The resampling distances used during the resampling
65. y to process a pair of images Sections 4 to 10 detail each function available in COSI Corr their chronology reflects more or less the chronology presented in section 3 This documentation was produced with TeXnicCenter http texniccenter sourceforge net using the MikTex distribution http www miktex org 1 2 Who Will Use This Document This documentation is aimed at scientists whose interest is in working with optical remotely sensed images aerials or satellites Users are likely to be Earth scientists looking for seismic ground deformations glacier flows sand dune displacements slow landslides or more generally looking for horizontal changes between multi temporal images Users do not need to have programming background but will need some familiarities with the concepts and vocabulary of remote sensing A basic knowledge of the ENVI software will be useful as COSI Corr is integrated in ENVI 1 3 About COSI Corr The COSI Corr software has been developed by Frangois Ayoub S bastien Leprince and Jean Philippe Avouac PI and is an implementation of the procedures described in e S Leprince S Barbot F Ayoub and J P Avouac Automatic and Precise Ortho rectification Coreg istration and Subpixel Correlation of Satellite Images Application to Ground Deformation Measure ments IEEE Transactions on Geoscience and Remote Sensing vol 45 no 6 pp 1529 1558 2007 Leprince et al 2007 e F Ayoub S Leprince

User`s Guide to COSI-CORR Co-registration of Optically Sensed

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