Residential Collegefalse
Status已發表Published
Blind quality assessment of compressed images via pseudo structural similarity
Xiongkuo Min1; Guangtao Zhai1; Ke Gu1; Yuming Fang2; Xiaokang Yang1; Xiaolin Wu1; Jiantao Zhou3; Xianming Liu4
2016-08-25
Conference NameIEEE International Conference on Multimedia & Expo (ICME)
Source PublicationProceedings - IEEE International Conference on Multimedia and Expo
Volume2016-August
Conference DateJUL 11-15, 2016
Conference PlaceSeattle, WA
Abstract

Block-based compression causes severe pseudo structures. We find that the pseudo structures of images compressed by different levels show some degree of similarity. So we propose to evaluate the quality of compressed images via the similarity between pseudo structures of two images. To obtain a 'reference' image, we introduce the most distorted image (MDI), which is derived from the distorted image and suffers from the highest degree of compression. The proposed pseudo structural similarity (PSS) model calculates the similarity between pseudo structures of the distorted image and MDI. Pseudo structures of the distorted image become similar to the MDI's under the condition of severe compression. Via comparative tests, the proposed PSS model, on one hand, is shown to be comparable to state-of-the-art competitors, and on the other hand, it is not only good at assessing natural scene images but also performs the best in the hotly-researched screen content image (SCI) database. It deserves to mention that PSS is able to boost the performance of mainstream general-purpose no-reference (NR) quality measures.

KeywordBlockiness Iqa Most Distorted Image Pseudo Structural Similarity Screen Content Image
DOI10.1109/ICME.2016.7552955
URLView the original
Indexed ByCPCI-S
Language英語English
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000389574300098
Scopus ID2-s2.0-84987670130
Fulltext Access
Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Faculty of Science and Technology
Affiliation1.Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, China
2.School of Information Technology, Jiangxi University of Finance and Economics, China
3.Department of Computer and Information Science, University of Macau, China
4.School of Computer Science and Technology, Harbin Institute of Technology, China
Recommended Citation
GB/T 7714
Xiongkuo Min,Guangtao Zhai,Ke Gu,et al. Blind quality assessment of compressed images via pseudo structural similarity[C], 2016.
APA Xiongkuo Min., Guangtao Zhai., Ke Gu., Yuming Fang., Xiaokang Yang., Xiaolin Wu., Jiantao Zhou., & Xianming Liu (2016). Blind quality assessment of compressed images via pseudo structural similarity. Proceedings - IEEE International Conference on Multimedia and Expo, 2016-August.
Files in This Item: Download All
File Name/Size Publications Version Access License
Blind_quality_assess(834KB)会议论文 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Xiongkuo Min]'s Articles
[Guangtao Zhai]'s Articles
[Ke Gu]'s Articles
Baidu academic
Similar articles in Baidu academic
[Xiongkuo Min]'s Articles
[Guangtao Zhai]'s Articles
[Ke Gu]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Xiongkuo Min]'s Articles
[Guangtao Zhai]'s Articles
[Ke Gu]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Blind_quality_assessment_of_compressed_images_via_pseudo_structural_similarity.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.