Dictionary-Based Image Denoising by Fused-Lasso Atom Selection
2014 ◽
Vol 2014
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pp. 1-10
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Keyword(s):
We proposed an efficient image denoising scheme by fused lasso with dictionary learning. The scheme has two important contributions. The first one is that we learned the patch-based adaptive dictionary by principal component analysis (PCA) with clustering the image into many subsets, which can better preserve the local geometric structure. The second one is that we coded the patches in each subset by fused lasso with the clustering learned dictionary and proposed an iterative Split Bregman to solve it rapidly. We present the capabilities with several experiments. The results show that the proposed scheme is competitive to some excellent denoising algorithms.
2014 ◽
Vol 73
(1)
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pp. 263-272
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Keyword(s):
Keyword(s):
2019 ◽
Vol 13
(7)
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pp. 1405-1412
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Keyword(s):
2016 ◽
Vol 23
(4)
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pp. 434-438
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2014 ◽
Vol 571-572
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pp. 753-756
2016 ◽
Vol 6
(1)
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pp. 194-203
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2016 ◽
Vol 21
(1)
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pp. 60-65
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