Towards anovel perceptual color difference metric using circular processing of hue components

This paper introduces a novel metric for image difference prediction, capable of handling color data. The proposed metric, namely, color difference index based on circular hue, is a full-reference based scheme, which independently processes achromatic and chromatic differences of two input color images. Within the framework, chromatic information is analyzed using two perceptual attributes, hue and chroma information, simulating human visual system mechanism. Unlike conventional approaches where the periodic nature of hue is disregarded, we propose to estimate hue difference by adopting theory of circular statistics. Performance of the proposed solution is validated using benchmark image quality assessment databases. Experimental results indicate the effectiveness of the proposed metric against a wide range of distortions, especially on chromatic distortions, making it better suited for color gamut mapping applications.