Neural network adaptive digital image screen halftoning (DISH) based on wavelet transform preprocessing

Harold H. Szu; Yingping Zhang; Mingui Sun; Ching-Chung Li

doi:10.1117/12.170080

15 March 1994 Neural network adaptive digital image screen halftoning (DISH) based on wavelet transform preprocessing

Harold H. Szu, Yingping Zhang, Mingui Sun, Ching-Chung Li

Proceedings Volume 2242, Wavelet Applications; (1994) https://doi.org/10.1117/12.170080
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

Artificial neural networks (ANN) can be used to process digital image screen halftoning (DISH), designed to be adaptive to the local variation of image intensity based on the wavelet transform (WT) preprocessing of the local gradient at each pixel. Our preliminary digital simulation results have shown an improved multiresolution visual effect of the bilevel representation of a gray-scale image. An interesting device concept is to build a fast 'WT chip' of order (N) with a smart 'neurochip' for DISH applications, in order to achieve an nonuniformly enhanced dot matrix printing.

Citation Download Citation

Harold H. Szu, Yingping Zhang, Mingui Sun, and Ching-Chung Li "Neural network adaptive digital image screen halftoning (DISH) based on wavelet transform preprocessing", Proc. SPIE 2242, Wavelet Applications, (15 March 1994); https://doi.org/10.1117/12.170080

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