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Autore principale: Gilles, Jerome
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2411.00894
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author Gilles, Jerome
author_facet Gilles, Jerome
contents In this paper, we investigate theoretically the behavior of Meyer's image cartoon + texture decomposition model. Our main results is a new theorem which shows that, by combining the decomposition model and a well chosen Littlewood-Paley filter, it is possible to extract almost perfectly a certain class of textures. This theorem leads us to the construction of a parameterless multiscale texture separation algorithm. Finally, we propose to extend this algorithm into a directional multiscale texture separation algorithm by designing a directional Littlewood-Paley filter bank. Several experiments show the efficiency of the proposed method both on synthetic and real images.
format Preprint
id arxiv_https___arxiv_org_abs_2411_00894
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Multiscale texture separation
Gilles, Jerome
Image and Video Processing
Computer Vision and Pattern Recognition
Functional Analysis
In this paper, we investigate theoretically the behavior of Meyer's image cartoon + texture decomposition model. Our main results is a new theorem which shows that, by combining the decomposition model and a well chosen Littlewood-Paley filter, it is possible to extract almost perfectly a certain class of textures. This theorem leads us to the construction of a parameterless multiscale texture separation algorithm. Finally, we propose to extend this algorithm into a directional multiscale texture separation algorithm by designing a directional Littlewood-Paley filter bank. Several experiments show the efficiency of the proposed method both on synthetic and real images.
title Multiscale texture separation
topic Image and Video Processing
Computer Vision and Pattern Recognition
Functional Analysis
url https://arxiv.org/abs/2411.00894