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Proceedings Paper

Polarimetric segmentation of SAR imagery
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Paper Abstract

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 for typical high-resolution, polarimetric SAR data gathered by the Lincoln Laboratory 35-GHz airborne sensor.

Paper Details

Date Published: 1 August 1991
PDF: 24 pages
Proc. SPIE 1471, Automatic Object Recognition, (1 August 1991); doi: 10.1117/12.44870
Show Author Affiliations
Michael C. Burl, Lincoln Lab./MIT (United States)
Leslie M. Novak, Lincoln Lab./MIT (United States)


Published in SPIE Proceedings Vol. 1471:
Automatic Object Recognition
Firooz A. Sadjadi, Editor(s)

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