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Hauptverfasser: Galiano, Gonzalo, Velasco, Julián
Format: Preprint
Veröffentlicht: 2013
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Online-Zugang:https://arxiv.org/abs/1311.2191
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author Galiano, Gonzalo
Velasco, Julián
author_facet Galiano, Gonzalo
Velasco, Julián
contents Nonlocal filters are simple and powerful techniques for image denoising. In this paper, we give new insights into the analysis of one kind of them, the Neighborhood filter, by using a classical although not very common transformation: the decreasing rearrangement of a function (the image). Independently of the dimension of the image, we reformulate the Neighborhood filter and its iterative variants as an integral operator defined in a one-dimensional space. The simplicity of this formulation allows to perform a detailed analysis of its properties. Among others, we prove that the filter behaves asymptotically as a shock filter combined with a border diffusive term, responsible for the staircaising effect and the loss of contrast.
format Preprint
id arxiv_https___arxiv_org_abs_1311_2191
institution arXiv
publishDate 2013
record_format arxiv
spellingShingle Neighborhood filters and the decreasing rearrangement
Galiano, Gonzalo
Velasco, Julián
Computer Vision and Pattern Recognition
68U10
Nonlocal filters are simple and powerful techniques for image denoising. In this paper, we give new insights into the analysis of one kind of them, the Neighborhood filter, by using a classical although not very common transformation: the decreasing rearrangement of a function (the image). Independently of the dimension of the image, we reformulate the Neighborhood filter and its iterative variants as an integral operator defined in a one-dimensional space. The simplicity of this formulation allows to perform a detailed analysis of its properties. Among others, we prove that the filter behaves asymptotically as a shock filter combined with a border diffusive term, responsible for the staircaising effect and the loss of contrast.
title Neighborhood filters and the decreasing rearrangement
topic Computer Vision and Pattern Recognition
68U10
url https://arxiv.org/abs/1311.2191