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arXiv · 1704.07063

A Dual Sparse Decomposition Method for Image Denoising

Hong Sun·Chen-guang Liu·Cheng-wei Sang
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Abstract

This article addresses the image denoising problem in the situations of strong noise. We propose a dual sparse decomposition method. This method makes a sub-dictionary decomposition on the over-complete dictionary in the sparse decomposition. The sub-dictionary decomposition makes use of a novel criterion based on the occurrence frequency of atoms of the over-complete dictionary over the data set. The experimental results demonstrate that the dual-sparse-decomposition method surpasses state-of-art denoising performance in terms of both peak-signal-to-noise ratio and structural-similarity-index-metric, and also at subjective visual quality.

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Hong Sun, Chen-guang Liu, Cheng-wei Sang. 2017-04-24. A Dual Sparse Decomposition Method for Image Denoising. https://arxiv.org/abs/1704.07063

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