Image Quality Assessment Based on Multi-Order Local Features Description, Modeling and Quantification-Reference-Cited by-同舟云学术

Image Quality Assessment Based on Multi-Order Local Features Description, Modeling and Quantification

Published:2017 Issue:6 Volume:E100.D Page:1303-1315
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

DING Yong¹,ZHAO Xinyu¹,ZHANG Zhi²,DAI Hang³

Affiliation:

1. College of Information Science and Electronic Technology, Zhejiang University

2. Department of Electrical and Information Technology, Lund University

3. Department of Computer Science, University of York

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E100.D/6/E100.D_2016EDP7244/_pdf

Reference52 articles.

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3. [3] K. Ma, T. Zhao, K. Zeng, and Z. Wang, “Objective quality assessment for color-to-gray image conversion,” IEEE Trans. Image Process., vol.24, no.12, pp.4673-4685, Dec. 2015.

4. [4] E.C. Larson and D.M. Chandler, “Most apparent distortion: Full-reference image quality assessment and the role of strategy,” J. Electron. Imag., vol.19, no.1, pp.011006:1011006:21, Jan. 2010.

5. [5] W. Lin and C.-C.J. Kuo, “Perceptual visual quality metrics: A survey,” J. Vis. Commun. and Imag. Repr., vol.22, no.4, pp.297-312, May 2011.

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