Image Denoising with Modified Grey Wolf Optimizer

Year 2018, Volume: 6 Issue: 4, 962 - 982, 01.08.2018

Hüseyin Avni Ardaç , Pakize Erdoğmuş

https://doi.org/10.29130/dubited.435783

Cited By: 2

Abstract

In this study, image denoising has
been realized with with the one of the recent Nature-Inspired optimization
algorithms, Grey Wolf Optimizer(GWO). GWO is one of the recent most studied
continous optimization algorithm which performs better than the other
algorithms. In this study, ten test images have been selected and gaussian  noise has been added  with some variance values.  After the noisy images have been attained,
these noisy images have been filtered with convulation in spatial domain. Filter
coefficents have been trained with GWO, Modified Grey Wolf Optimizer(MGWO) and
Genetic Algorithm(GA). Weiner filtering is also applied on the images for image
denosing. The results show that Weiner Filter outperforms GWO trained filters
on most of the images.  MGWO performance
is better then GWO and the results show that MGWO can also be used as an
alternative method for image denoising. In the future studies, adaptive MGWO
can be enhanced for much more succesfull image denoising process.

Keywords

GWO, MGWO, GA, Image Denoising

Düzenlenmiş Gri Kurt Optimizasyon Algoritması ile Gürültü Temizleme

Abstract

Bu çalışmada, yakın
zamanda doğadan esinlenen optimizasyon algoritmalarından biri olan Gri Kurt
Optimizasyonu(GWO) ile görüntülerdeki gürültülerin temizlenmesi
gerçekleştirilmiştir. GWO, diğer algoritmalardan daha iyi performans gösteren,  son zamanlarda en çok çalışılan sürekli
optimizasyon algoritmasından biridir. Bu çalışmada on test görüntüsü seçilmiş
ve bazı varyans değerleri ile gauss gürültüsü eklenmiştir. Gürültülü görüntüler
elde edildikten sonra, bu gürültülü görüntüler  uzamsal  alanda konvülasyon ile filtrelenmiştir. Filtre
katsayıları GWO, Modifiye Gri Kurt Optimizasyonu (MGWO) ve Genetik Algoritma
(GA) ile eğitilmiştir. Elde edilen sonuçlara göre Weiner filter çoğu resimde
daha başarılı sonuçlar vermiştir.  MGWO’nun performansı GWO’dan daha iyidir ve
sonuçlar MGWO’nun gürültü gidermede alternatif bir metot olarak
kullanılabileceğini göstermiştir. Gelecekteki çalışmalarda daha başarılı gürültü
temizleme işlemi için adaptif MGWO geliştirilebilir.

Keywords

GWO, MGWO, GA, Gürültü Temizleme

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