Tetrolet-based reduced reference image quality assessment approach
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | Tetrolet-based reduced reference image quality assessment approach |
| Type de publication | Conference Paper |
| Year of Publication | 2014 |
| Auteurs | Abdelouahad AAit, Alibouch B, Omari M, Hassouni MEl, Cherifi H |
| Conference Name | 2014 INTERNATIONAL CONFERENCE ON MULTIMEDIA COMPUTING AND SYSTEMS (ICMCS) |
| Publisher | IEEE |
| Conference Location | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| ISBN Number | 978-1-4799-3824-7 |
| Mots-clés | GGD, KLD, RRIQA, Tetrolet transform |
| Résumé | In this paper, we propose a new reduced reference image quality assessment (RRIQA) scheme. For this purpose, we use a statistical-based method in a new adaptive Haar wavelet transform domain, called Tetrolet. Firstly, we decompose the reference and distorted images and we obtain the Tetrolet coefficients for each image. Secondly, we use a marginal Generalized Gaussian Density (GGD) to model each subband coefficients. Finally, the distortion measure is computed using the Kullback Leibler Divergence (KLD) between GGD Probability density function (PDFs). Experimental results show the efficiency of the proposed method when comparing to those reported in the literature. |