On color image quality assessment using natural image statistics
Computer Vision and Pattern Recognition
2014-12-01 v1
Abstract
Color distortion can introduce a significant damage in visual quality perception, however, most of existing reduced-reference quality measures are designed for grayscale images. In this paper, we consider a basic extension of well-known image-statistics based quality assessment measures to color images. In order to evaluate the impact of color information on the measures efficiency, two color spaces are investigated: RGB and CIELAB. Results of an extensive evaluation using TID 2013 benchmark demonstrates that significant improvement can be achieved for a great number of distortion type when the CIELAB color representation is used.
Keywords
Cite
@article{arxiv.1411.7682,
title = {On color image quality assessment using natural image statistics},
author = {Mounir Omari and Mohammed El Hassouni and Hocine Cherifi and Abdelkaher Ait Abdelouahad},
journal= {arXiv preprint arXiv:1411.7682},
year = {2014}
}