2014/11/29 by Mounir Omari, Abdelkaher Ait Abdelouahad, Omari, Mounir +5
Computer Science · Engineering · Physics and Astronomy · #Advanced Image Fusion Techniques #Color Science and Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image and Video Quality Assessment
paper · pdf · doi:10.48550/arxiv.1412.0111
openalex publication_date 2014/11/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper deals with color image quality assessment in the reduced-reference\nframework based on natural scenes statistics. In this context, we propose to\nmodel the statistics of the steerable pyramid coefficients by a Multivariate\nGeneralized Gaussian distribution (MGGD). This model allows taking into account\nthe high correlation between the components of the RGB color space. For each\nselected scale and orientation, we extract a parameter matrix from the three\ncolor components subbands. In order to quantify the visual degradation, we use\na closed-form of Kullback-Leibler Divergence (KLD) between two MGGDs. Using\n"TID 2008" benchmark, the proposed measure has been compared with the most\ninfluential methods according to the FRTV1 VQEG framework. Results demonstrates\nits effectiveness for a great variety of distortion type. Among other benefits\nthis measure uses only very little information about the original image.\n