Paper
1 April 1998 Application of the neural networks based on multivalued neurons in image processing and recognition
Igor N. Aizenberg, Naum N. Aizenberg
Author Affiliations +
Proceedings Volume 3307, Applications of Artificial Neural Networks in Image Processing III; (1998) https://doi.org/10.1117/12.304648
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States
Abstract
Multi-valued neurons are the neural processing elements with complex-valued weights, huge functionality (it is possible to implement arbitrary mapping described by partial-defined multiple-valued function on the single neuron), fast converged learning algorithms. Such features of the multi- valued neurons may be used for solution of the different kinds of problems. Special kind of neural network with multi-valued neurons for image recognition will be considered in the paper. Such a network analyzes the spectral coefficients corresponding to low frequencies. A quickly converged learning algorithm and example of face recognition are also presented. The next application of multi-valued neurons proposed in this paper is their using as basic elements of a cellular neural network. Such an approach makes it possible to implement high effective non- linear multi-valued filters. These filters are very effective for reduction of Gaussian, uniform and speckle noise. They are also highly effective for solution of the frequency correction problem. A correction of the high and medium spatial frequencies using multi-valued filters leads to highly effective extraction of details and local contrast enhancement. Two methods for solution of the super- resolution problem using prediction of high frequency coefficients on multi-valued neuron, and correction of the high frequency part of spectrum by multi-valued filtering are proposed also.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Igor N. Aizenberg and Naum N. Aizenberg "Application of the neural networks based on multivalued neurons in image processing and recognition", Proc. SPIE 3307, Applications of Artificial Neural Networks in Image Processing III, (1 April 1998); https://doi.org/10.1117/12.304648
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Cited by 8 scholarly publications.
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KEYWORDS
Neurons

Nonlinear filtering

Neural networks

Image filtering

Detection and tracking algorithms

Electronic filtering

Gaussian filters

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