Color image quantization using weighted distortion measure of HVS color activity

Abstract

Color quantization is to design a color palette having almost no noticeably perceived difference between original and quantized images. In this paper, to design such a palette, the color quantization algorithm is considered in two parts. The selection of a proper distortion measure and the design of an optimal palette. The proper selection of distortion measure in the quantization is important to image quality. Since the human eye is the final judge of image quality, it is desirable to use a perception-based distortion measure. Thus we developed an activity-weighted distortion measure considering color visual sensitivity and absorbance of human visual system (HVS) depending on each color component in the local region of image. Then using the distortion measure, a hierarchical quantization algorithm is proposed. The algorithm consists of initial and subdivision steps both to reduce computation time and to minimize the distortion based on spatial masking effect of HVS. The experimental results show that the proposed algorithm shows better visual quality and less computation time comparing to the conventional algorithms.