Polarimetric Segmentation of Synthetic Aperture Radar Imagery
نویسنده
چکیده
This paper considers the problem of clutter segmentation in fully polarimetric, high resolution, synthetic aperture radar (SAR) imagery. The goal of segmentation is to partition an image into regions of homogeneous terrain types (grass regions, tree regions, roads, etc.). Three approaches to segmentation are examined: (1) the optimal polarimetric classifier, (2) the optimal normalized polarimetric classifier, and (3) the polarimetric whitening filter (PWF) classifier. Segmentation performance results are presented using high resolution, polarimetric SAR data gathered by the Lincoln Laboratory 33 GHz airborne sensor.
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