Residential College | false |
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 Name | IEEE International Conference on Multimedia & Expo (ICME) |
Source Publication | Proceedings - IEEE International Conference on Multimedia and Expo |
Volume | 2016-August |
Conference Date | JUL 11-15, 2016 |
Conference Place | Seattle, 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. |
Keyword | Blockiness Iqa Most Distorted Image Pseudo Structural Similarity Screen Content Image |
DOI | 10.1109/ICME.2016.7552955 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Computer Science ; Engineering |
WOS Subject | Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
WOS ID | WOS:000389574300098 |
Scopus ID | 2-s2.0-84987670130 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE Faculty of Science and Technology |
Affiliation | 1.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. |
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