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A Novel Nonlinear Regression Approach for Efficient and Accurate Image Matting
IEEE Signal Processing Letters
Current image matting approaches are often implemented based upon color samples under various local assumptions. In this letter, a novel image matting algorithm is investigated by treating the alpha matting as a regression problem. Specifically, we learn spatially-varying relations between pixel features and alpha values using support vector regression. Via the learning-based approach, limitations caused by local image assumptions can be greatly relieved. In addition, the computed confidencedoi:10.1109/lsp.2013.2274874 fatcat:juj6xyqg2ffaln22lbn3ydbnny