Image Restoration Based on Adaptive Directional Regularization
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概要
- 論文の詳細を見る
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 filters 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 doesnt depend on parameters selection. The convexity conditions as well as the convergence conditions are derived for the proposed algorithm.
- （社）電子情報通信学会の論文
- 2009-12-01
著者
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TANAKA TOSHIHISA
Department of Clinical Neuroscience & Psychiatry, Osaka University Graduate School of Medicine
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Ahmed Omer
Department Of Electrical And Electronic Engineering Tokyo University Of Agriculture And Technology
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