Dithered color quantization

Image quantization and digital halftoning are fundamental problems in compu ter graphics, which arise when displaying high-color images on non-truecolo r devices. Both steps am generally performed sequentially and, in most case s, independent of each other Color quantization with a pixel-wise defined d istortion measure and the dithering process with its local neighborhood opt imize different quality criteria or, frequently, follow a heuristic without reference to any quality measure. In this paper we propose a new method to simultaneously quantize and dither color images. The method is based on a vigorous cost-function approach whi ch optimizes a quality criterion, derived from a generic model of human per ception. A highly efficient algorithm for optimization based on a multiscal e method is developed for the dithered color quantization cost function. Th e quality criterion and the optimization algorithms are evaluated on a repr esentative set of artificial and real-world images us well as on a collecti on of icons. A significant image quality improvement is observed compared t o standard color reduction approaches.