Segmentation-based target detection in SAR

This paper proposes a target-detection scheme based on prior segmentation of the image. Introducing the prior knowledge of image structure provided by the previous segmentation eliminates many false target detections from background structure. The performance of the new scheme is shown to be identical to an ideal one-parameter CFAR for constant background. With real clutter backgrounds the background detection probability with the new scheme is considerably lower than with one-parameter CFAR, without any loss in target detection. We also demonstrate that for smaller false alarm probabilities, the original segmentation yields nearly all the detections achieved by segmentation-based target detection.