Residential College | false |
Status | 已發表Published |
A Hybrid Structural Sparse Error Model for Image Deblocking | |
Zhiyuan Zha1; Xin Yuan2; Jiantao Zhou3; Ce Zhu4; Bihan Wen1 | |
2020-05 | |
Conference Name | 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 |
Source Publication | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Volume | Volume 2020-May |
Pages | 2493-2497 |
Conference Date | 04-08 May 2020 |
Conference Place | Barcelona, Spain |
Country | Spain |
Publisher | IEEE |
Abstract | Inspired by the image nonlocal self-similarity (NSS) prior, structural sparse representation (SSR) models exploit each group as the basic unit for sparse representation, which have achieved promising results in various image restoration applications. However, conventional SSR models only exploited the group within the input degraded (internal) image for image restoration, which can be limited by over-fitting to data corruption. In this paper, we propose a novel hybrid structural sparse error (HSSE) model for image deblocking. The proposed HSSE model exploits image NSS prior over both the internal image and external image corpus, which can be complementary in both feature space and image plane. Moreover, we develop an alternating minimization with an adaptive parameter setting strategy to solve the proposed HSSE model. Experimental results demonstrate that the proposed HSSE-based image deblocking algorithm outperforms many state-of-the-art image deblocking methods in terms of objective and visual perception. |
Keyword | Hybrid Structural Sparse Error Nonlocal Self-similarity Structural Sparse Representation Image Deblocking |
DOI | 10.1109/ICASSP40776.2020.9053968 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Acoustics ; Engineering |
WOS Subject | Acoustics ; Engineering, Electrical & Electronic |
WOS ID | WOS:000615970402147 |
Scopus ID | 2-s2.0-85088534432 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE Faculty of Science and Technology |
Corresponding Author | Bihan Wen |
Affiliation | 1.School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore 639798 2.Nokia Bell Labs, 600 Mountain Avenue, Murray Hill, NJ, 07974, USA 3.Department of Computer and Information Science, University of Macau, Macau 999078, China 4.School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China |
Recommended Citation GB/T 7714 | Zhiyuan Zha,Xin Yuan,Jiantao Zhou,et al. A Hybrid Structural Sparse Error Model for Image Deblocking[C]:IEEE, 2020, 2493-2497. |
APA | Zhiyuan Zha., Xin Yuan., Jiantao Zhou., Ce Zhu., & Bihan Wen (2020). A Hybrid Structural Sparse Error Model for Image Deblocking. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Volume 2020-May, 2493-2497. |
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