Changes between Version 28 and Version 29 of ACompletePhotogrammetricOSSIMtoolForAutomaticDSMenerationUsingMultiViewOpticalAndSARimages


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Timestamp:
Aug 20, 2016, 5:57:56 AM (6 years ago)
Author:
martidi
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  • ACompletePhotogrammetricOSSIMtoolForAutomaticDSMenerationUsingMultiViewOpticalAndSARimages

    v28 v29  
    327327THE ADDITION THAT MY PROJECT BROUGHT TO THE SOFTWARE:
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    329 My work has complemented OSSIM with some processing algorithms for high resolution satellite optical and SAR images. With my addition, now it is possible to generate automatically DSMs from SAR imagery using an iterative coarse-to-fine approach, to take advantage of iterative solutions at gradually increasing resolution. Furthermore, I have implemented automatic masks generation for foreshortening and layover areas in SAR images: so far, it is possible to generate a DSM from SAR imagery (automatically detecting the ascending or descending orbit), masked for foreshortening and layover areas in order to correct from potential geometric distortions. Moreover, in order to obtain a more accurate DSM by exploiting the redundancy of multiple information, I have implemented the DSMs merging on the basis of mean and standard deviation of ascending and descending stacks and of the automated generated masks for foreshortening and layover areas in SAR images.
     329My work has complemented OSSIM with some processing algorithms for high resolution satellite optical and SAR images. With my addition, now it is possible to generate automatically DSMs from SAR imagery (so far tested only with TerraSAR imagery with external generated RPC files) using an iterative coarse-to-fine approach, to take advantage of iterative solutions at gradually increasing resolution. Furthermore, I have implemented automatic masks generation for foreshortening and layover areas in SAR images: so far, it is possible to generate a DSM from SAR imagery (automatically detecting the ascending or descending orbit), masked for foreshortening and layover areas in order to correct from potential geometric distortions. Moreover, in order to obtain a more accurate DSM by exploiting the redundancy of multiple information, I have implemented the DSMs merging on the basis of mean and standard deviation of ascending and descending stacks and of the automated generated masks for foreshortening and layover areas in SAR images.
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