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In this paper, we present a regularization approach on discrete graph spaces for perceptual image segmentation via semisupervised learning. In this approach, first, a spectral clustering method is embedded and extended into regularization on discrete graph spaces. In consequence, the spectral graph clustering is optimized and smoothed by integrating top-down and bottom-up processes via semi-supervised learning. Second, a designed nonlinear diffusion filter is used to maintain semi-superviseddoi:10.1109/icme.2007.4285067 dblp:conf/icmcs/ZhengH07 fatcat:u46wpwjorraendk6gpparbb5ru