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A Hybrid Structural Sparse Error Model for Image Deblocking
Zhiyuan Zha1; Xin Yuan2; Jiantao Zhou3; Ce Zhu4; Bihan Wen1
2020-05
Conference Name2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Source PublicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
VolumeVolume 2020-May
Pages2493-2497
Conference Date04-08 May 2020
Conference PlaceBarcelona, Spain
CountrySpain
PublisherIEEE
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.

KeywordHybrid Structural Sparse Error Nonlocal Self-similarity Structural Sparse Representation Image Deblocking
DOI10.1109/ICASSP40776.2020.9053968
URLView the original
Indexed ByCPCI-S
Language英語English
WOS Research AreaAcoustics ; Engineering
WOS SubjectAcoustics ; Engineering, Electrical & Electronic
WOS IDWOS:000615970402147
Scopus ID2-s2.0-85088534432
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Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Faculty of Science and Technology
Corresponding AuthorBihan Wen
Affiliation1.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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