The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Este artigo aborda problemas que aparecem em algoritmos de restauração baseados na utilização de Tikhonov e regularização de variação total bilateral (BTV). A regularização anterior assume que a informação anterior tem distribuição gaussiana que de fato falha nas bordas, enquanto a regularização posterior depende altamente dos parâmetros do filtro bilateral selecionado. Para superar esses problemas, propomos uma regularização localmente adaptativa. No algoritmo proposto, utilizamos funções gerais de regularização direcional com pesos adaptativos. Os pesos adaptativos são estimados a partir de patches locais com base na propriedade da imagem parcialmente restaurada. Ao contrário da regularização de Tikhonov, ela pode evitar suavidade nas bordas usando pesos adaptativos. Além disso, diferentemente da regularização BTV, a função de regularização proposta não depende da seleção de parâmetros. As condições de convexidade, bem como as condições de convergência são derivadas para o algoritmo proposto.
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Osama AHMED OMER, Toshihisa TANAKA, "Image Restoration Based on Adaptive Directional Regularization" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 12, pp. 3344-3354, December 2009, doi: 10.1587/transfun.E92.A.3344.
Abstract: This paper addresses problems appearing in restoration algorithms based on utilizing both Tikhonov and bilateral total variation (BTV) regularization. The former regularization assumes that prior information has Gaussian distribution which indeed fails at edges, while the later regularization highly depends on the selected bilateral filter's parameters. To overcome these problems, we propose a locally adaptive regularization. In the proposed algorithm, we use general directional regularization functions with adaptive weights. The adaptive weights are estimated from local patches based on the property of the partially restored image. Unlike Tikhonov regularization, it can avoid smoothness across edges by using adaptive weights. In addition, unlike BTV regularization, the proposed regularization function doesn't depend on parameters' selection. The convexity conditions as well as the convergence conditions are derived for the proposed algorithm.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.3344/_p
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@ARTICLE{e92-a_12_3344,
author={Osama AHMED OMER, Toshihisa TANAKA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Image Restoration Based on Adaptive Directional Regularization},
year={2009},
volume={E92-A},
number={12},
pages={3344-3354},
abstract={This paper addresses problems appearing in restoration algorithms based on utilizing both Tikhonov and bilateral total variation (BTV) regularization. The former regularization assumes that prior information has Gaussian distribution which indeed fails at edges, while the later regularization highly depends on the selected bilateral filter's parameters. To overcome these problems, we propose a locally adaptive regularization. In the proposed algorithm, we use general directional regularization functions with adaptive weights. The adaptive weights are estimated from local patches based on the property of the partially restored image. Unlike Tikhonov regularization, it can avoid smoothness across edges by using adaptive weights. In addition, unlike BTV regularization, the proposed regularization function doesn't depend on parameters' selection. The convexity conditions as well as the convergence conditions are derived for the proposed algorithm.},
keywords={},
doi={10.1587/transfun.E92.A.3344},
ISSN={1745-1337},
month={December},}
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TY - JOUR
TI - Image Restoration Based on Adaptive Directional Regularization
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 3344
EP - 3354
AU - Osama AHMED OMER
AU - Toshihisa TANAKA
PY - 2009
DO - 10.1587/transfun.E92.A.3344
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2009
AB - This paper addresses problems appearing in restoration algorithms based on utilizing both Tikhonov and bilateral total variation (BTV) regularization. The former regularization assumes that prior information has Gaussian distribution which indeed fails at edges, while the later regularization highly depends on the selected bilateral filter's parameters. To overcome these problems, we propose a locally adaptive regularization. In the proposed algorithm, we use general directional regularization functions with adaptive weights. The adaptive weights are estimated from local patches based on the property of the partially restored image. Unlike Tikhonov regularization, it can avoid smoothness across edges by using adaptive weights. In addition, unlike BTV regularization, the proposed regularization function doesn't depend on parameters' selection. The convexity conditions as well as the convergence conditions are derived for the proposed algorithm.
ER -