Low-rank approach for image nonblind deconvolution with variance estimation

CORC > 长春光学精密机械与物理研究所 > 中国科学院长春光学精密机械与物理研究所 > 中科院长春光机所知识产出

	Low-rank approach for image nonblind deconvolution with variance estimation
	Yang, H.; G. S. Hu; Y. Q. Wang and X. T. Wu
刊名	Journal of Electronic Imaging
	2015
卷号	24 期号:6 页码:11
英文摘要	We develop a low-rank approach for image restoration by exploiting the image's nonlocal self-similarity. We assume that the matrix stacked by the vectors of nonlocal similar patches is of low rank and has sparse singular values. Based on this assumption, we propose a new image deconvolution algorithm that decouples the deblurring and denoising steps. Specifically, in the deblurring step, we involve a regularized inversion of the blur in the Fourier domain, which amplifies and colors the noise and corrupts the image information. Hence, in the denoising step, a singular-value decomposition of similar packed patches is used to efficiently remove the colored noise. Furthermore, we derive an approach to update the estimation of noise variance for setting the threshold parameter at each iteration. Experimental results clearly show that the proposed algorithm outperforms many state-of-the-art deblurring algorithms such as iterative decoupled deblurring BM3D in terms of both improvement in signal-to-noise-ratio and visual perception quality. (C) 2015 SPIE and IS&T
收录类别	SCI ; EI
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/55502]
专题	长春光学精密机械与物理研究所_中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Yang, H.,G. S. Hu,Y. Q. Wang and X. T. Wu. Low-rank approach for image nonblind deconvolution with variance estimation[J]. Journal of Electronic Imaging,2015,24(6):11.
APA	Yang, H.,G. S. Hu,&Y. Q. Wang and X. T. Wu.(2015).Low-rank approach for image nonblind deconvolution with variance estimation.Journal of Electronic Imaging,24(6),11.
MLA	Yang, H.,et al."Low-rank approach for image nonblind deconvolution with variance estimation".Journal of Electronic Imaging 24.6(2015):11.