Combined Shearlet Shrinkage and Total Variation Minimization for Image Denoising

被引:0
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作者
Zohre Mousavi
Mehrdad Lakestani
Mohsen Razzaghi
机构
[1] Isfahan University of Technology,Department of Mathematical Sciences
[2] University of Tabriz,Department of Applied Mathematics, Faculty of Mathematical sciences
[3] Mississippi State University,Department of Mathematics and Statistics
关键词
Shearlet; Total variation; Additive operator splitting; Image processing; Image denoising; 94A08; 68U10;
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摘要
In this paper, a TV-based shearlet shrinkage is proposed for discontinuity-preserving denoising using a combination of shearlet with a total variation scheme. For TV denoising numerical procedure, we use two approaches. In the first approach, we apply semi-implicit method for total variation. To solve Euler–Lagrange equation associated with total variation, we use additive operator splitting (AOS) scheme. This approach has good effect on suppressing the pseudo-Gibbs and shearlet-like artifacts and is very efficient for reducing iterations. In the second approach, we use Split Bregman iteration method. This techniques converges very quickly and in combine by shearlet shrinkage produce good results.
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页码:31 / 37
页数:6
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