Prior knowledge has been considered as valuable supplementary information in many image processing techniques. In this paper, we take the input image itself as the guidance prior and develop a novel fuzzy clustering algorithm to segment it by adding a new term to the objective function of Fuzzy C-Means. The new term comes from Guided Filter for its capability in noise suppression and edge-preserving smoothing. As a result, the memberships derived from the new objective function incorporate the guidance information from the image to be segmented. In this way, the segmentation result retains more subtle details on the boundaries of segments. According to experimental results, the proposed method shows good performance in image segmentation tasks especially for images with high noise rates.

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guidance information edgepreserving memberships method guided filter image segmentation tasks objective function boundaries of fuzzy clustering algorithm noise suppression

Li Guo,C. L. Philip Chen,Long Chen,Yingwen Wu,.Image Guided Fuzzy C-Means for Image Segmentation. 19 (6),1660–1669.

Li Guo, et al."Image Guided Fuzzy C-Means for Image Segmentation" 19

Li Guo,C. L. Philip Chen,Long Chen,Yingwen Wu,"Image Guided Fuzzy C-Means for Image Segmentation"