Title :
Neural implementation of ARMA type filters for image restoration
Author :
Stajniak, Andrzej ; Szostakowski, Jarostaw
Author_Institution :
Inst. of Control & Ind. Electron., Warsaw Univ. of Technol., Poland
Abstract :
We present a novel neural implementation of the autoregressive moving average (ARMA) type filters for image deblurring. Our filter is designed on the basis of a known blur system. As the neural net, we used a multilayer perceptron. Due to connection of the parallel processing and nonlinear characteristics in the neural networks, we hoped to reduced the influence of noise and roundoff errors. We present the construction of different learning patterns for this net. Some practical examples are shown
Keywords :
IIR filters; autoregressive moving average processes; backpropagation; filtering theory; image restoration; multilayer perceptrons; noise; parallel processing; roundoff errors; ARMA type filters; IIR filter; autoregressive moving average; backpropagation; blur system; image deblurring; image restoration; learning patterns; multilayer perceptron; neural implementation; neural net; neural networks; noise; nonlinear characteristics; parallel processing; roundoff errors; Degradation; Filtering; IIR filters; Image restoration; Industrial electronics; Multi-layer neural network; Multilayer perceptrons; Neural networks; Parallel processing; Pixel;
Conference_Titel :
Image Processing, 1995. Proceedings., International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-7310-9
DOI :
10.1109/ICIP.1995.537530
