Lei Wang, Xiu-Fen Ye, Gaobo Wang, and Lin Wang
Hierarchical MRF, sonar image, grey distribution, imagesegmentation
Hierarchical Markov random field (MRF) algorithm has been widely used in sonar image segmentation. To improve the algorithm speed, we abandon the method which describes different regions using regional distribution of grey distribution model and propose a new method in which sonar image was described using grey value statistics. In the proposed method, considering the characteristic of sonar image and the flexibility of this method, the number of category for segmentation can be changed from three to two to improve the calculation speed. They are region of interest (ROI) and background regions respectively. Firstly, C-Means algorithm is used to pre-segment image into three categories. The target and shadow regions are classified as ROI. Secondly, hierarchical MRF model is deployed to segment images into two regions. Finally, the ROI is re-segmented into two regions using greyscale threshold method. Results show that the proposed method can effectively reduce model parameters and computation cost, and the real-time segmentation of sonar image can be achieved.
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