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A fast subspace method for image deblurring
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AI
DOI：10.1016/j.amc.2009.08.033.png)
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Abstract
En 中文
Image deblurring problems appear frequently in astronomical image analysis. For image deblurring problems, it is reasonable to add a non-negativity constraint because of the physical meaning of the image. Previous research works are mainly full-space methods, i.e., solving a regularized optimization problem in a full space. To solve the problem more efficiently, we propose a subspace method. We first formulate the problem from full space to subspace and then use an interior-point trust-region method to solve it. The numerical experiments show that this method is suitable for ill-posed image deblurring problems. (C) 2009 Elsevier Inc. All rights reserved.
Keywords:
Image deblurring
Subspace
Interior-point method
Trust region
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