CNN paradigm based multilevel halftoning of digital images

• Published in: IEEE transactions on circuits and systems. 2, Analog and digital signal processing Vol. 44; no. 1; pp. 50 - 53
• Main Authors: Bakic, P.R., Vujovic, N.S., Brzakovic, D.P., Kostic, P.D., Reljin, B.D.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.1997; Institute of Electrical and Electronics Engineers
• Subjects: Applied sciences; Cellular neural networks; Digital filters; Digital images; Exact sciences and technology; Finite impulse response filter; Frequency; Image processing; Information, signal and communications theory; Mean square error methods; Resonator filters; Sampling methods; Signal processing; Signal processing algorithms; Signal sampling; Telecommunications and information theory; Grey level image; Image processing; Selection criterion; Digital image; Neural network; Algorithm; Half tone image; Mean square error
• ISSN: 1057-7130
• DOI: 10.1109/82.559369

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.