Convergence Theorems for the Non-Local Means Filter
classification
📊 stat.AP
keywords
filterchoiceconvergencemeansnon-localparameterstheoremsadditive
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In this paper, we establish convergence theorems for the Non-Local Means Filter in removing the additive Gaussian noise. We employ the techniques of "Oracle" estimation to determine the order of the widths of the similarity patches and search windows in the aforementioned filter. We propose a practical choice of these parameters which improve the restoration quality of the filter compared with the usual choice of parameters.
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