IPSJ Transactions on Computer Vision and Applications
Online ISSN : 1882-6695
ISSN-L : 1882-6695
Image Denoising with Sparsity Distillation
Satoshi KawataNao Mishima
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ジャーナル フリー

2015 年 7 巻 p. 50-54

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抄録
We propose a new image denoising method with shrinkage. In the proposed method, small blocks in an input image are projected to the space that makes projection coefficients sparse, and the explicitly evaluated sparsity degree is used to control the shrinkage threshold. On average, the proposed method obtained higher quantitative evaluation values (PSNRs and SSIMs) compared with one of the state-of-the-art methods in the field of image denoising. The proposed method removes random noise effectively from natural images while preserving intricate textures.
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© 2015 by the Information Processing Society of Japan
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