Automatic analysis of change detection of multi-temporal ERS-2 SAR images by using two-threshold EM and MRF algorithms

摘要

To automatically detect and analyze the surface change in the urban area from multi-temporal SAR images, an algorithm of two-threshold expectation maximum (EM) and Markov random field (MRF) is developed. Difference of the SAR images demonstrates variation of backseattering caused by the surface change all over the image pixels. Two thresholds are obtained by the EM iterative process and categorized to three classes: enhanced scattering, reduced scattering and unchanged regimes. Initializing from theEM result, the iterated conditional modes (ICM) algorithm of the MRF is then used to analyze the detection of contexture change in the urban area. As art example, two images of the ERS-2 SAR in 1996 and 2002 over the Shanghai City are studied.