Abstract
This paper addresses the statistical segmentation of SAR (Synthetic Aperture Radar) image combining PM (Perona Malik) nonlinear diffusion model and MRF (Markov Random Field) model. First, the original SAR image is filtered using the modified PM nonlinear diffusion model, in which the diffusion coefficients along the tangent direction and the normal direction are approximated and simplified. Afterwards, the filtered image is segmented using MRF model, in which the clique potential is computed using both the label configuration and the intensity information. The proposed method is marked by PM-MRF for short. Experimental results show that PM-MRF competes favorably with the traditional one to segment SAR image homogeneously.
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