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Proceedings Paper

Wiener filter-based change detection for SAR imagery
Author(s): Maria Tates; Nasser Nasrabadi; Heesung Kwon; Carl White
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Paper Abstract

In this paper we propose a Wiener filter-based change detection algorithm for the detection of mines in Synthetic Aperture Radar (SAR) imagery. By computing second order statistics, the Wiener filter-based method has demonstrated improved performance over Euclidean distance. It is more robust to the presence of highly correlated speckle noise, misregistration errors, and nonlinear variations in the two SAR scenes. These variations may result from differences in the data acquisition systems and varying conditions during the different data collect times. A method very similar to the Mahalanobis distance was also implemented to detect mines in SAR images and has shown similar performance to the Wiener filter-based method. We present results in the form of receiver operating characteristics (ROC) curves, comparing simple Euclidean difference change detection, Mahalanobis difference-based change detection, and the proposed Wiener filter-based change detection in both global and local implementations.

Paper Details

Date Published: 17 May 2006
PDF: 8 pages
Proc. SPIE 6237, Algorithms for Synthetic Aperture Radar Imagery XIII, 62370N (17 May 2006); doi: 10.1117/12.665945
Show Author Affiliations
Maria Tates, U.S. Army Research Lab. (United States)
Morgan State Univ. (United States)
Nasser Nasrabadi, U.S. Army Research Lab. (United States)
Heesung Kwon, U.S. Army Research Lab. (United States)
Carl White, Morgan State Univ. (United States)


Published in SPIE Proceedings Vol. 6237:
Algorithms for Synthetic Aperture Radar Imagery XIII
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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