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A relaxation neural network model for optimal multi-level image representation by local-parallel computations

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1 Author(s)
Sonehara, N. ; ATR Auditory & Visual Perception Res. Labs., Kyoto, Japan

A relaxation neural network model is proposed to solve the multi-level image representation problem by energy minimization in local and parallel computations. This network iteratively minimizes the computational energy defined by the local error in neighboring picture elements. This optimization method can generate high quality binary and multi-level images depending on local features, and can be implemented efficiently on parallel computers

Published in:

Neural Networks for Signal Processing [1991]., Proceedings of the 1991 IEEE Workshop

Date of Conference:

30 Sep-1 Oct 1991