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	IMAGE DEBLOCKING USING GROUP-BASED SPARSE REPRESENTATION AND QUANTIZATION CONSTRAINT PRIOR
	Zhang, Jian ; Ma, Siwei ; Zhang, Yongbing ; Gao, Wen
	2015
关键词	Image deblocking sparse representation blocking artifact reduction quantization constraint JPEG DECOMPRESSION TRANSFORM DOMAIN RESTORATION ARTIFACTS STANDARD REDUCTION DCT
英文摘要	To alleviate the conflict between bit reduction and quality preservation, deblocking as a post-processing strategy is an attractive and promising solution without changing existing codec. In this paper, in order to reduce blocking artifacts and obtain high-quality image, image deblocking is formulated as an optimization problem via maximum a posteriori framework, and a novel algorithm for image deblocking using group-based sparse representation (GSR) and quantization constraint (QC) prior is proposed. GSR prior is utilized to simultaneously enforce the intrinsic local sparsity and the nonlocal self-similarity of natural images, while QC prior is explicitly incorporated to ensure a more reliable and robust estimation. A new split Bregman iteration based method with adaptively adjusted regularization parameter is developed to solve the proposed optimization problem for image deblocking. The parameter-adaptive advantage enables the whole algorithm more attractive and practical. Experiments manifest that the proposed image deblocking algorithm improves current state-of-the-art results by a large margin in both PSNR and visual perception.; EI; CPCI-S(ISTP); 306-310; 2015-December
语种	英语
出处	2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
DOI标识	10.1109/ICIP.2015.7350809
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/436430]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhang, Jian,Ma, Siwei,Zhang, Yongbing,et al. IMAGE DEBLOCKING USING GROUP-BASED SPARSE REPRESENTATION AND QUANTIZATION CONSTRAINT PRIOR. 2015-01-01.

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