Visual Information Fidelity in evaluating Retinex enhancement algorithms

Developing image enhancement algorithms require that there exists a proper evaluation scheme to compare different algorithms. Most objective algorithms fail because they are not designed for the subjective nature of the enhancement problem. This necessitates an evaluation scheme that would correlate with scores provided by a group of human observers. In this paper, we consider the quality assessment of images which are visually improved using various versions of Retinex algorithm. The objective of this paper is twofold. To check the suitability of available current distortion based quality assessment methods to evaluate nonlinear image enhancement algorithms and to check if consistently better objective scores are obtained for better Retinex algorithms. To this end, we find correlation between mean opinion score obtained from subjective evaluation and objective quality score for each of the methods under consideration.