Title :
Multiple-valued feedback neural networks for image restoration
Author :
Chen, Zhong-Yu ; Desai, M.
Author_Institution :
Div. of Eng., Texas Univ., San Antonio, TX, USA
Abstract :
We present a new type of Hopfield feedback network for image restoration, called the multiple-valued neural networks (MVFN). The main advantages of this model are that it can store patterns having different grey levels, and that it can store binary patterns with much less neurons than that of a Hopfield binary NN. We apply this new network for noise removal on two different images
Keywords :
Hopfield neural nets; content-addressable storage; image restoration; learning (artificial intelligence); noise; Hopfield binary neural network; Hopfield feedback network; binary patterns storage; content associative memory; grey levels; image restoration; learning algorithm; multiple-valued feedback neural networks; neurons; noise removal; patterns storage; Associative memory; CADCAM; Computer aided manufacturing; Convergence; Hopfield neural networks; Image restoration; Neural networks; Neurofeedback; Neurons; Noise level;
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
DOI :
10.1109/ICIP.1996.559608
