DocumentCode
3333622
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
fYear
1991
fDate
30 Sep-1 Oct 1991
Firstpage
473
Lastpage
482
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks for Signal Processing [1991]., Proceedings of the 1991 IEEE Workshop
Conference_Location
Princeton, NJ
Print_ISBN
0-7803-0118-8
Type
conf
DOI
10.1109/NNSP.1991.239494
Filename
239494
Link To Document