CNN paradigm based multilevel halftoning of digital images

An algorithm for displaying gray level images using a small number of fixed quantization levels is proposed. The algorithm, called multilevel halftoning, is based on the Cellular Neural Networks (CNN) paradigm. It tracks the CNN transient outputs and selects the image which is subjectively perceived to be the best when reduced to the allowed number of gray levels. The selection criterion is based on the "visually compensated" mean square error that takes into account the specifics of the human visual system. The results of the proposed algorithm were validated in subjective quality experiments with human subjects.