Title :
Blur identification and image restoration using a multilayer neural network
Author :
Cho, Chao-Ming ; Don, Hon-Son
Author_Institution :
Dept. of Electr. Eng., State Univ. of New York, Stony Brook, NY, USA
Abstract :
A neural network model combining an adaptive heteroassociative network and an adaptive autoassociative network with a random Gaussian process is proposed to identify the noncausal blur function and to restore the blurred image at the same time. The noisy blurred images are modeled as continuous associative networks, where the autoassociative part determines the image model coefficients and the heteroassociative part determines the blur function of the system. The estimation and restoration are implemented by using an iterative steepest descent algorithm to minimize the error functions of the networks. Experiment results demonstrate that effective identification and restoration can be performed
Keywords :
adaptive systems; content-addressable storage; iterative methods; neural nets; pattern recognition; picture processing; random processes; adaptive autoassociative network; adaptive heteroassociative network; blur identification; continuous associative networks; error function minimization; image restoration; iterative steepest descent algorithm; multilayer neural network; noncausal blur function; random Gaussian process; Adaptive systems; Autoregressive processes; Chaos; Degradation; Gaussian processes; Image restoration; Iterative algorithms; Multi-layer neural network; Neural networks; Parameter estimation;
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
DOI :
10.1109/IJCNN.1991.170774