Using an exact radial basis function artificial neural network for impulsive noise suppression from highly distorted image databases


Civicioglu P. , Alci M. , Besdok E.

ADVANCES IN INFORMATION SYSTEMS, PROCEEDINGS, cilt.3261, ss.383-391, 2004 (SCI İndekslerine Giren Dergi) identifier

  • Cilt numarası: 3261
  • Basım Tarihi: 2004
  • Dergi Adı: ADVANCES IN INFORMATION SYSTEMS, PROCEEDINGS
  • Sayfa Sayıları: ss.383-391

Özet

In this paper, a new filter, RM, which is based on exact radial basis function artificial neural networks, is proposed for the impulsive noise suppression from highly distorted images. The RM uses Chi-Squared based goodness-of-fit test in order to find corrupted pixels more accurately. The proposed filter shows a high performance at the restoration of images distorted by impulsive noise. The extensive simulation results show that the proposed filter achieves a superior performance to the other filters mentioned in this paper in the cases of being effective in noise suppression and detail preservation, especially when the noise density is very high.