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-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 3261
  • Basım Tarihi: 2004
  • Dergi Adı: ADVANCES IN INFORMATION SYSTEMS, PROCEEDINGS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED)
  • Sayfa Sayıları: ss.383-391
  • Erciyes Üniversitesi Adresli: Evet

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.