Image Quality Assessment Based on Multi-scale Geometric Analysis

Authors:
Mingna Liu;Xin Yang;Yanfeng Shang
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, P.R. China;Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, P.R. China;Department of Electronics and Informatics, Vrije Universiteit Brussel, IBBT, Brussel, Belgium 1050
Venue:
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Year:
2009

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Abstract

A novel objective full-reference image quality assessment metric based on Multi-scale Geometric Analysis (MGA) of contourlet transform is proposed. Contourlet transform has excellent properties for image representation, such as multiresolution, localization and directionality, which are the key characteristics of human vision system. Utilizing multiresolution and directionality of MGA, we extract the distortion of structural information from different vision scale and edge direction. The degradation of image quality is evaluated based on the defined energy of structural distortion. Performance experiments are made on professional image quality database with five different distortion types. Compared with some state-of-the-art measures, the results demonstrate that the proposed method improves accuracy and robustness of image quality prediction.