Neural implementation of ARMA type filters for image restoration

  • Authors:

  • A. Stajniak;J. Szostakowski

  • Affiliations:

  • -;-

  • Venue:
  • ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
  • Year:
  • 1995

Quantified Score

Hi-index 0.01

Visualization

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.