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Robust Locally Linear Analysis with Applications to Image Denoising and Blind Inpainting
SIAM Journal of Imaging Sciences
We study the related problems of denoising images corrupted by impulsive noise and blind inpainting (i.e., inpainting when the deteriorated region is unknown). Our basic approach is to model the set of patches of pixels in an image as a union of low-dimensional subspaces, corrupted by sparse but perhaps large magnitude noise. For this purpose, we develop a robust and iterative method for single subspace modeling and extend it to an iterative algorithm for modeling multiple subspaces. We provedoi:10.1137/110843642 fatcat:ad7gswrsyffldiiw63tby5423m