Dictionary learning approach for image deconvolution with variance estimation

	Dictionary learning approach for image deconvolution with variance estimation
	Yang H.; Zhu M.; Wu X. T.; Zhang Z. B.; Huang H. Y.
	2014
发表期刊	Applied Optics
ISSN	ISBN/1559-128X
卷号	53 期号:25 页码:5677-5684
摘要	In this paper, we propose a new dictionary learning approach for image deconvolution, which effectively integrates the Fourier regularization and dictionary learning technique into the deconvolution framework. Specifically, we propose an iterative algorithm with the decoupling of the deblurring and denoising steps in the restoration process. In the deblurring step, we involve a regularized inversion of the blur in the Fourier domain. Then we remove the colored noise using a dictionary learning method in the denoising step. In the denoising step, we propose an approach to update the estimation of noise variance for dictionary learning. We will show that this approach outperforms several state-of-the-art image deconvolution methods in terms of improvement in signal-to-noise ratio and visual quality. (C) 2014 Optical Society of America
收录类别	SCI ; EI
语种	英语
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/43893
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Yang H.,Zhu M.,Wu X. T.,et al. Dictionary learning approach for image deconvolution with variance estimation[J]. Applied Optics,2014,53(25):5677-5684.
APA	Yang H.,Zhu M.,Wu X. T.,Zhang Z. B.,&Huang H. Y..(2014).Dictionary learning approach for image deconvolution with variance estimation.Applied Optics,53(25),5677-5684.
MLA	Yang H.,et al."Dictionary learning approach for image deconvolution with variance estimation".Applied Optics 53.25(2014):5677-5684.

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