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. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Liu, M., Yang, X., & Shang, Y. (2009). Image quality assessment based on multi-scale geometric analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5716 LNCS, pp. 807–815). https://doi.org/10.1007/978-3-642-04146-4_86
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