A procedure is presented in the stcrco matching of digital synthetic aperture radar (SAR) imagery obtaincd from NASA's shutlle imaging radar B (SIR-B) experiment.The coherent nature o f SAR means that speckle is an inevitable by-product. The presence of speckle in SAR imagery makcs thc conventional use of region growing stereo-matching algorithms untenable. To overcome the problem of speckle, a technique was developed whercby stcrco matching was performed in a course-to-fine pyramidal fashion.I t is shown that the stcrco-matchcd extent obtaincd with this technique can give an approximate three-rold increase in stcrco coverage, i f a suitable specklereduction filter is also cmploycd.
This paper describes a procedure developed at University College London for the automatic stereo matching of SAR imagery from NASA's Seasat satellite. The method employed uses Gruen's least squares correlation technique to improve the match accuracy of randomly generated points as they are cascaded down an image pyramid, coupled with a sheet growing mechanism in order to produce a dense array of points. The overall result of the cascading procedure is the totally automatic production of a dense digital disparity model [DDM].
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