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Target/shadow segmentation and aspect estimation in synthetic aperture radar imagery

This paper discusses algorithms that are useful for the classification of targets in SAR imagery. Two algorithms are presented for segmenting a target region from background clutter; one based on constant false alarm rate detection, and another histogram based technique. The histogram based technique is extended to extract shadow regions associated with a target. A method is then presented for estimating the orientation of segmented targets. These algorithms are applied to SAR imagery from the Lincoln Lab ADTS and MSTAR datasets. The aspect estimate is shown to be superior to estimates obtained from the direction of the axis of least inertia.