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In this paper, a new framework for texture reconstruction of missing areas, which exist all over the target image, is presented. The framework is based on a projection onto convex sets (POCS) algorithm including a novel constraint. In the proposed method, a nonlinear eigenspace of each cluster obtained by texture classification is applied to the constraint. Furthermore, by monitoring the errors converged by the POCS algorithm, selection of the optimal cluster for the target texture includingdoi:10.1109/icip.2007.4379256 dblp:conf/icip/OgawaH07 fatcat:6jyjopjy7jfjxhtclo5b5is4ai