Using an exact radial basis function artificial neural network for impulsive noise suppression from highly distorted image databases
ADVANCES IN INFORMATION SYSTEMS, PROCEEDINGS, cilt.3261, ss.383-391, 2004 (SCI-Expanded)
- 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.