Local adaptivity to variable smoothness for exemplar-based image denoising and representation

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How researchers see this paper

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From Heuristic Optimization to Dictionary Learning: A Review and Comprehensive Comparison of Image Denoising Algorithms (2014, background): “[24] proposed a neighborhood filter, which is similar to NLM but the weights are determined by the intensity difference of patches.”
From Local Kernel to Nonlocal Multiple-Model Image Denoising (2009, methodology): “We would like to thank Julien Mairal, Jerome Boulanger and Charles Kervrann for providing us the experimental results of their algorithms.”
Optimal Spatial Adaptation for Patch-Based Image Denoising (2006, methodology): “In all our experiments, we have chosen image patches of 9 9 pixels and set the algorithm parameters as follows: , and (see also [31]).”
Patch-Based Nonlocal Functional for Denoising Fluorescence Microscopy Image Sequences (2010, background): “where is a positive constant (we choose ; see [58]).”