Title :
A relaxation neural network model for optimal multi-level image representation by local-parallel computations
Author :
Sonehara, Noboru
Author_Institution :
ATR Auditory & Visual Perception Res. Labs., Kyoto, Japan
fDate :
30 Sep-1 Oct 1991
Abstract :
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
Keywords :
image processing; neural nets; energy minimization; local error; local-parallel computations; optimal multi-level image representation; relaxation neural network model; Computer errors; Computer networks; Concurrent computing; Image converters; Image representation; Laboratories; Neural networks; Neurons; Quantization; Visual perception;
Conference_Titel :
Neural Networks for Signal Processing [1991]., Proceedings of the 1991 IEEE Workshop
Conference_Location :
Princeton, NJ
Print_ISBN :
0-7803-0118-8
DOI :
10.1109/NNSP.1991.239494
