Distance Measure Based Change Detectors for Polarimetric SAR Imagery

Abstract

Change detection based on multi-temporal <small>SAR</small> images is a fundamental process in many practical applications. Popular <small>SAR</small> change detectors include ratio and logarithmic-ratio (log-ratio) operators, and those based on a statistical similarity between temporal images. The ratio and log-ratio operators are not ideal for polarimetric <small>SAR</small> (<small>POLSAR</small>) images, as only the intensity or amplitude information is used. Change detectors based on similarity comparison of probability distribution functions are difficult to implement and not reliable because of the uncertainties in estimating distribution parameters. Our research aims to find a reliable and computationally simple change detector from among three typical polarimetric distance measures. The change detection potential and abilities of these distance measures are analyzed from a mathematical point of view, and then compared through a test dataset composed of two <small>RADARSAT-2</small> fine-quad polarized images. The symmetric revised Wishart (<small>SRW</small>) distance, originally developed for image segmentation, is found to be an effective change detector. Based on the test data, the change map derived from the <small>SRW</small> distance achieves 93.24 percent change rate and 5.67 percent false alarm rate. Furthermore, the eigendecompostion of the <small>SRW</small> distance is given for the first time, which uncovers the linkage of the <small>SRW</small> distance with the scattering mechanisms and the corresponding amplitudes embedded in two polarimetric covariance matrices, forming a theoretical explanation for the superiority of the <small>SRW</small> distance as a change detector. Our research indicates the general applicability of the <small>SRW</small> distance for <small>POLSAR</small> change detection.