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18 April 2010 The effect of synthetic aperture radar image resolution on target discrimination
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This paper details the effect of spatial resolution on target discrimination in Synthetic Aperture Radar (SAR) images. Multiple SAR image chips, containing targets and non-targets, are used to test a baseline Automatic Target Recognition (ATR) system with reduced spatial resolution obtained by lowering the pixel count or synthesizing a degraded image. The pixel count is lowered by averaging groups of adjoining pixels to form a new single value. The degraded image is synthesized by low-pass-filtering the image frequency space and then lowering the pixel count. To train a linear classifier, a two-parameter Constant False Alarm Rate (CFAR) detector is tested, and three different types of feature spaces, are used: size, contrast, and texture. The results are scored using the Area Under the Receiver Operator Characteristic (AUROC) curve. The CFAR detector is shown to perform better at lower resolution. All three feature sets together performed well with the degradation of resolution; separately the sets had different performances. The texture features performed best because they do not rely on the number of pixels on the target, while the size features performed the worst for the same reason. The contrast features yielded improved performance when the resolution was slightly reduced.
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John E. McGowan, Steven C. Gustafson, Julie Ann Jackson, and Andrew J. Terzuoli Jr. "The effect of synthetic aperture radar image resolution on target discrimination", Proc. SPIE 7699, Algorithms for Synthetic Aperture Radar Imagery XVII, 76990X (18 April 2010);

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