DocumentCode :
306410
Title :
Biologically motivated neural computing in early vision processing
Author :
Guan, L. ; Anderson, J.A. ; Sutton, J.P.
Author_Institution :
Dept. of Electr. Eng., Sydney Univ., NSW, Australia
Volume :
2
fYear :
1996
fDate :
14-17 Oct 1996
Firstpage :
1138
Abstract :
We introduce a network of networks (NoN) model to solve image processing problems in early vision. The method is motivated by the fact that natural image formation is a local process, and thus processing can be accomplished by a globally coordinated, local parallel processing structure, readily implemented by the hierarchical cluster architecture of the NoN model. The modeling is very powerful in that it achieves high quality adaptive processing, and virtually eliminates the computational difference between inhomogeneous and homogeneous conditions. Computer simulations show that this method is able to provide fast, quality image processing in early vision
Keywords :
computer vision; neural nets; parallel processing; quadratic programming; adaptive processing; early vision processing; hierarchical cluster architecture; image formation; image processing; image regularization; network of networks model; neural computing; parallel processing; quadratic programming; Biology computing; Computer vision; Degradation; Image processing; Image sensors; Neural networks; Optimization methods; Parallel processing; Pixel; Sensor arrays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1996., IEEE International Conference on
Conference_Location :
Beijing
ISSN :
1062-922X
Print_ISBN :
0-7803-3280-6
Type :
conf
DOI :
10.1109/ICSMC.1996.571244
Filename :
571244
Link To Document :
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