Two-stage image denoising based on sparse representations

被引：0
|
作者：
He, Yan-Min [1 ]
Gan, Tao [2 ]
Chen, Wu-Fan [1 ]
机构：
[1] School of Automation Engineering, University of Electronic Science and Technology of China
[2] School of Electronic Engineering, University of Electronic Science and Technology of China
来源：
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2012年 / 34卷 / 09期
关键词：
Dictionary pruning; Dictionary training; Image processing; Sparse representation;
D O I：
10.3724/SP.J.1146.2012.00136
中图分类号：
学科分类号：
摘要：
It remains a challenging task to restore the image which is contaminated with heavy noise. In this paper, an image denoising method is proposed based on sparse representations. In the dictionary training stage, a matching criterion based on correlation coefficient is introduced and a dictionary pruning scheme is proposed to tackle the conflicting issues of structure extraction and artifact suppression. Experimental results show that the proposed method achieves significant improvements over the previous sparse denoising methods and outperforms the state-of-the-art methods in terms of both objective and subjective quality at high noise level.
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收藏
页码：2268 / 2272
页数：4
相关论文
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