SAR Images Processing Based on Gibbs-MRF and Connected Clustering

This paper proposes a new method of restoration and segmentation of SAR image. The radar cross-section (RCS) for intensity SAR images is estimated based on Gibbs Markov random fields and simulated annealing. Further, it puts forward to segment SAR image into target and shadow with the theory of connectivity in digital morphology. In this paper, Gibbs Markov random field models and simulated annealing used together for SAR images processing are discussed for the first time; a simple and effective method is presented for SAR images segmentation using the connected cluster model of pixels intensity value relevance in the neighborhood of SAR image pixel space, and obtains good segment results.