CNN PARADIGM-BASED MULTILEVEL HALF-TONING OF DIGITAL IMAGES

An algorithm for displaying gray level images using a small number of fixed quantization levels is proposed. The algorithm, called multileve l halftoning, is based on the Cellular Neural Network (CNN) paradigm. It tracks the CNN transient outputs and selects the image which is sub jectively perceived to he the best when reduced to the allowed number of gray levels. The selection criterion is based on the ''visually com pensated'' mean square error that takes into account the specifics of the human visual system. The results of the proposed algorithm were va lidated in subjective quality experiments with human subjects.