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Superpixel is widely used in image processing. And among the methods forsuperpixel generation, clustering-based methods have a high speed and a goodperformance at the same time. However, most clustering-based superpixel methodsare sensitive to noise. To solve these problems, in this paper, we firstanalyze the features of noise. Then according to the statistical features ofnoise, we propose a novel centroid update approach to enhance the robustness ofclustering-based superpixel methods. Besides, we propose a novelsuperpixel-based edge detection method. The experiments on BSD500 dataset showthat our approach can significantly enhance the performance of clustering-basedsuperpixel methods in noisy environment. Moreover, we also show that ourproposed edge detection method outperforms other classical methods.

A novel centroid update approach for clustering-based superpixel methods and superpixel-based edge detection