SUPERPIXEL SEGMENTATION BASED ON GRADIENT AND MANIFOLD
In today's image processing tasks,the super pixel is often used as a method of dimensionality reduction for image as well as the basis of edge optimization.A super-pixel segmentation method based on gradient and manifold distance is proposed to solve the problem of experience-dependent segment number and discrete point of existing methods.It estimated the suitable number of superpixels for images adaptively,making segmentation for details more accurate and reducing over-segmentation for background.Experiments were conducted on BSDS500 dataset.We achieved good performance in various indicators.Escpecially,the elimination of discrete points leads to the compact with huge improvement.
国家科技期刊平台
NSTL
万方数据
维普
