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Perturbation of the eigenvectors of the graph Laplacian: Application to image denoising
Institution:1. Department of Electrical Engineering, University of Colorado at Boulder, Boulder, CO, United States;2. Department of Diagnostic Radiology, Yale University, CT, United States
Abstract:Patch-based denoising algorithms currently provide the optimal techniques to restore an image. These algorithms denoise patches locally in “patch-space”. In contrast, we propose in this paper a simple method that uses the eigenvectors of the Laplacian of the patch-graph to denoise the image. Experiments demonstrate that our denoising algorithm outperforms the denoising gold-standards. We provide an analysis of the algorithm based on recent results on the perturbation of kernel matrices (El Karoui, 2010) 1], 2], and theoretical analyses of patch denoising algorithms (Levin et al., 2012) 3], (Taylor and Meyer, 2012) 4].
Keywords:Graph Laplacian  Eigenvector perturbation  Random kernel matrix  Patch  Image denoising
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