Image segmentation algorithm based on spatial correlation
基于空间相关性的图像分割算法研究

This paper presented a full use of spatial image correlation to achieve efficient fast image segmentation method. First of all, it used mean shift image segmentation algorithm to formate an excessive segmentation, so that it made these areas to maintain the desired edge and spatial correlation part. Then, it used the graph structure of the region adjacency graph instead of segmentation. Like K-means algorithm, iterative belief propagation algorithm had the advantages of fast convergence was used to minimize the cost function, integrate over segmentation and obtain the final segmentation result. Based on the segmentation of the region rather than the image pixel, image clustering segmentation method could reduce the noise sensitivity, while improving the quality of image segmentation. Comparing with FCM and MRF algorithm, the new algorithm in entropy evaluation standard especially complex scene images shows a better performance.