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Sparse learning based methods are effective for image restoration applications since they make use of texture priors learned by pre-trained over-complete dictionaries. However, sparse learning based methods are extremely slow due to complexity of sparse decomposition and a large number of image patches to process. In this paper, we introduce a fast approximation for LASSO (Least Absolute Shrinkage...
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