2009
DOI: 10.1109/tip.2009.2028250
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Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems

Abstract: This paper studies gradient-based schemes for image denoising and deblurring problems based on the discretized total variation (TV) minimization model with constraints. We derive a fast algorithm for the constrained TV-based image deburring problem. To achieve this task, we combine an acceleration of the well known dual approach to the denoising problem with a novel monotone version of a fast iterative shrinkage/thresholding algorithm (FISTA) we have recently introduced. The resulting gradient-based algorithm … Show more

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Cited by 1,787 publications
(1,621 citation statements)
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“…This can be realized in different ways, e.g., by the simple gradient descent reprojection algorithm in [15] or by faster multistep algorithms [6,50,63].…”
mentioning
confidence: 99%
“…This can be realized in different ways, e.g., by the simple gradient descent reprojection algorithm in [15] or by faster multistep algorithms [6,50,63].…”
mentioning
confidence: 99%
“…In the future work, we will address the issue of motion blur in two perspectives: 1) integrate deblurring techniques [43, 44] into our system; 2) provide a simple training process to familiarize blind users with the device to reduce motion blur. Our future work will also focus on evaluating the proposed system to recognize banknotes of different countries and transferring the method to mobile phones.…”
Section: Discussionmentioning
confidence: 99%
“…In this work, Eq. (7) is solved by the gradient-based recovery method [30,31], whose iteration form is given by…”
Section: A Conventional Landweber Iteration L1 Regularization and Tmentioning
confidence: 99%