Study of Sonar Image Segmentation Based on Markov Random Field

Aiming at the problems such as great noise disturbance and poor performance of traditional arithmetic in the field of underwater sonar image segmentation, based on analyzing grey-level distribution of sonar image and the Markov random fields theory (MRF), several groups of gray-level distribution model for shadow area and background area were introduced. The adaptive maximum-entropy arithmetic was introduced to initialize the segmentation, and the image pre-segmentation arithmetic based on fractal theory was presented. Performance of these models was simulated and analyzed. Simulation results indicate that the method given by this paper has good precision and great robustness. Furthermore, this method has little dependence on image pre-processing. The analyzed conclusions have guiding meaning for understanding and analysis of sonar image