A novel SAR fusion image segmentation method based on Markov Random Field

Markov Random Field (MRF) method is a popular technology in SAR image segmentation nowadays. It considers the statistical characteristics of SAR image and achieves optimal image segmentation result. In this paper, a novel SAR fusion image segmentation method based on MRF model is proposed. Firstly, the mechanism of MRF segmentation on single SAR image is studied. Secondly, the Maximum a Posterior (MAP) formula for SAR fusion image segmentation is deduced by supposing the two SAR images for fusion are statistically independent. Then the energy function of SAR fusion image segmentation is presented and the processing steps are given. At the end, computer simulation indicates that the performance of this new approach is much better than that of single SAR image segmentation based on MRF.