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Change detection is an essential step for synthetic aperture radar (SAR) image interpretation. We propose a change detection method that included a denoising method and a difference operator to improve the change precision. The SAR images are first transformed into logarithmic domain before filtering. And then, the log-intensity image is filtered by the iterative guided filter that is the combination of a traditional guided filter and iterative regularization technique. The operator based on the log-ratio (LR) and neighbourhood pixels is developed to generate the difference image, which can reflect the change trends between images effectively. The final image that consisted of changed pixels and unchanged pixels is obtained by using the fuzzy c-means (FCM) algorithm. The experimental results accomplished over two real SAR datasets demonstrate that the proposed method can improve the accuracy of change detection.

A SAR change detection method based on an iterative guided filter and the log mean ratio