A robust quality metric for color image quality assessment
In this paper, we propose a visual color image quality metric with full reference image for the evaluation of coding schemes. This metric is based on human visual system properties in order to get the best correspondence with human judgements. Contrary to some others objective criteria, it doesn't use any information on the type of degradations introduced by coding schemes. We use two main stages: the first one in order to compute visual representation of images (based on results from psychophysics experiments conducted in our laboratory) and the second in order to pool errors between visual representation of two images. We propose a new approach for this pooling stage based on the density of errors and their structure. We also show the interest of such pooling method. We compare results of the metric with human judgments on a database of 140 images distorted with 3 types of compression schemes (JPEG, JPEG2000 and a ROI-based algorithm). High performances are obtained leading to assure that the metric is robust, so this approach constitutes an alternative useful tool to PSNR for coding image searchers.