Impulsive noise suppression from highly corrupted images by using resilient neural networks

Besdok E., Civicioglu P., Alci M.

ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2004, cilt.3070, ss.670-675, 2004 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 3070
  • Basım Tarihi: 2004
  • Dergi Adı: ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2004
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED)
  • Sayfa Sayıları: ss.670-675
  • Erciyes Üniversitesi Adresli: Evet

Özet

A new impulsive noise elimination filter, entitled Resilient Neural Network based impulsive noise removing filter (RF), which shows a high performance at the restoration of images corrupted by impulsive noise, is proposed in this paper. The RF uses Chi-square goodness-of-fit test in order to find corrupted pixels more accurately. The corrupted pixels are replaced by new values which were estimated by using the proposed RF. 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.