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Journal of Electronic Imaging

Processing of noisy and small-detailed gray-scale images using cellular neural networks
Author(s): Igor N. Aizenberg
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Paper Abstract

Algorithms of filtering, edge detection, and extraction of details and their implementation using cellular neural networks (CNN) are developed in this paper. The theory of CNN based on universal binary neurons (UBN) is also developed. A new learning algorithm for this type of neurons is carried out. Implementation of low-pass filtering algorithms using CNN is considered. Separate processing of the binary planes of gray-scale images is proposed. Algorithms of edge detection and impulsive noise filtering based on this approach and their implementation using CNN-UBN are presented. Algorithms of frequency correction reduced to filtering in the spatial domain are considered. These algorithms make it possible to extract details of given sizes. Implementation of such algorithms using CNN is presented. Finally, a general strategy of gray-scale image processing using CNN is considered.

Paper Details

Date Published: 1 July 1997
PDF: 14 pages
J. Electron. Imag. 6(3) doi: 10.1117/12.269905
Published in: Journal of Electronic Imaging Volume 6, Issue 3
Show Author Affiliations
Igor N. Aizenberg, K.U. Leuven (Israel)

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