Target detection in SAR images via radiometric multi-resolution analysis

This paper presents a target detection method in synthetic aperture radar (SAR) images with radiometric multiresolution analysis (RMA). The idea is that target saliency can be efficiently computed by comparing the statistics of targets and those of the local background around them. In order to compute reliable statistics of targets, which usually involve a small number of pixels, RMA is adopted. The RMA preprocessing method performs well in stabilizing the statistical characteristics of SAR images. It can effectively restrain the speckle noise while keep the statistical characteristics of the original image. Based on the computed target saliency, adaptive decision thresholds are got by using the constant false alarm rate (CFAR) target detection framework. Our experiments on real SAR images show that the proposed method can achieve better performance compared with the traditional cell average-constant false alarm rate (CA-CFAR) method.