Title :
Applications of SOAR to monochromatic image restoration
Author :
Özturk, Yusuf ; Abut, Hüseyin
Author_Institution :
Dept. of Electr. & Comput. Eng., San Diego State Univ., CA, USA
Abstract :
This study proposes a novel autoassociator for associative storage of gray scale images. An autoassociator is a system capable of completing an incomplete pattern, when it is presented as part of a learned pattern. Patterns in the proposed associative architecture are gray scale images with integer values. The proposed system, based on a previously developed technique called “SOAR”, is superior to existing techniques using binary neural networks for associative storage of gray scale images in both the computational complexity and the processing unit requirements. The proposed system is parallel in nature and can be implemented using a synchronous or asynchronous parallel system with no added complexity
Keywords :
computational complexity; content-addressable storage; image restoration; learning (artificial intelligence); neural net architecture; parallel processing; SOAR; associative architecture; associative storage; asynchronous parallel system; autoassociator; binary neural networks; computational complexity; gray scale images; monochromatic image restoration; processing unit requirements; synchronous parallel system; Application software; Associative memory; Computational complexity; Computer architecture; Content addressable storage; Image restoration; Image storage; Neural networks; Pixel; Shape;
Conference_Titel :
Neural Networks for Signal Processing IX, 1999. Proceedings of the 1999 IEEE Signal Processing Society Workshop.
Conference_Location :
Madison, WI
Print_ISBN :
0-7803-5673-X
DOI :
10.1109/NNSP.1999.788155