Neural-network-aided design for image processing

Ilia Vitsnudel; Ran Ginosar; Yehoshua Y. Zeevi

doi:10.1117/12.50370

1 November 1991 Neural-network-aided design for image processing

Ilia Vitsnudel, Ran Ginosar, Yehoshua Y. Zeevi

Proceedings Volume 1606, Visual Communications and Image Processing '91: Image Processing; (1991) https://doi.org/10.1117/12.50370
Event: Visual Communications, '91, 1991, Boston, MA, United States

Abstract

A new concept of Neural Network-Aided Design (NN-AD) is presented. It is a hierarchical approach consisting of several concatenated stages of visual information processing that are designed by training neural networks (NN). Thus, NN-AD can be viewed as a general tool for the design of special filters in accordance with the specific task of image processing under consideration. The nonlinear filters are formatted by a supervised presentation of a proper set of input-output patterns. The principles of NN-AD design are illustrated by the examples of edge detection with subpixel resolution and of orientational processing for edge enhancement. The proposed NN-AD approach is found to be very robust with regard to various types of errors.

Citation Download Citation

Ilia Vitsnudel, Ran Ginosar, and Yehoshua Y. Zeevi "Neural-network-aided design for image processing", Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); https://doi.org/10.1117/12.50370

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