No-reference image quality assessment using structural activity

Authors:
Jing Zhang;Thinh M. Le;S. H. Ong;Truong Q. Nguyen
Affiliations:
Department of Electrical and Computer Engineering, National University of Singapore, Block E4-05-45, 4 Engineering Drive 3, Singapore 117576, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, Block E4-05-45, 4 Engineering Drive 3, Singapore 117576, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, Block E4-05-45, 4 Engineering Drive 3, Singapore 117576, Singapore and Division of Bioengineering, National Uni ...;Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093-0407, USA
Venue:
Signal Processing
Year:
2011

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Abstract

Presuming that human visual perception is highly sensitive to the structural information in a scene, we propose the concept of structural activity (SA) together with a model of SA indicator in a new framework for no-reference (NR) image quality assessment (QA) in this study. The proposed framework estimates image quality based on the quantification of the SA information of different visual significance. We propose some alternative implementations of SA indicator in this paper as examples to demonstrate the effectiveness of the SA-motivated framework. Comprehensive testing demonstrates that the model of SA indicator exhibits satisfactory performance in comparison with subjective quality scores as well as representative full-reference (FR) image quality measures.