Reduction in impulse noise in digital images through a new adaptive artificial neural network model
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Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, an adaptive artificial neural network model is developed in order to restore severely corrupted images. The proposed new and effective impulse noise reduction filter is named as adaptive neural network models with an algorithm based on artificial neural networks. Networks trained at different noise intensities get activated according to the intensity of the noise and estimate the most suitable neighboring pixel that can replace the corrupted pixel. The proposed algorithm reduces impulse noise effectively while also protecting the details. Experimental results show that the proposed algorithm performs better compared with other traditional filters.
Açıklama
Anahtar Kelimeler
Impulse Noise, Neural Network, Image Enhancement, Image Restoration
Kaynak
Neural Computing & Applications
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
26
Sayı
4
