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1 June 1991 Neural networks for halftoning of color images
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Proceedings Volume 1452, Image Processing Algorithms and Techniques II; (1991) https://doi.org/10.1117/12.45365
Event: Electronic Imaging '91, 1991, San Jose, CA, United States
Abstract
This paper illustrates the use of Hopfield neural networks to halftone color images. We define an error function which is the weighted sum of squared errors of the Fourier components of the original and halftoned images. The weights can be chosen to match the human visual system or other input/output transfer functions. The error function is minimized by using a neural network and solving its dynamical equation iteratively. FFTs are used to perform the necessary convolutions so that the computational requirements are reasonable even for large images.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Daniel T. Ling and Dieter Just "Neural networks for halftoning of color images", Proc. SPIE 1452, Image Processing Algorithms and Techniques II, (1 June 1991); https://doi.org/10.1117/12.45365
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