Yıl 2018, Cilt 6, Sayı 4, Sayfalar 962 - 982 2018-08-01

Image Denoising with Modified Grey Wolf Optimizer
Düzenlenmiş Gri Kurt Optimizasyon Algoritması ile Gürültü Temizleme

Hüseyin Avni Ardaç [1] , Pakize Erdoğmuş [2]

92 137

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.

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.

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Yazar: Hüseyin Avni Ardaç (Sorumlu Yazar)
Kurum: DÜZCE ÜNİVERSİTESİ, REKTÖRLÜK
Ülke: Turkey


Yazar: Pakize Erdoğmuş
Kurum: DÜZCE ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ
Ülke: Turkey


Bibtex @araştırma makalesi { dubited435783, journal = {Düzce Üniversitesi Bilim ve Teknoloji Dergisi}, issn = {}, eissn = {2148-2446}, address = {Düzce Üniversitesi}, year = {2018}, volume = {6}, pages = {962 - 982}, doi = {}, title = {Image Denoising with Modified Grey Wolf Optimizer}, key = {cite}, author = {Erdoğmuş, Pakize and Ardaç, Hüseyin Avni} }
APA Ardaç, H , Erdoğmuş, P . (2018). Image Denoising with Modified Grey Wolf Optimizer. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 6 (4), 962-982. Retrieved from http://dergipark.gov.tr/dubited/issue/38650/435783
MLA Ardaç, H , Erdoğmuş, P . "Image Denoising with Modified Grey Wolf Optimizer". Düzce Üniversitesi Bilim ve Teknoloji Dergisi 6 (2018): 962-982 <http://dergipark.gov.tr/dubited/issue/38650/435783>
Chicago Ardaç, H , Erdoğmuş, P . "Image Denoising with Modified Grey Wolf Optimizer". Düzce Üniversitesi Bilim ve Teknoloji Dergisi 6 (2018): 962-982
RIS TY - JOUR T1 - Image Denoising with Modified Grey Wolf Optimizer AU - Hüseyin Avni Ardaç , Pakize Erdoğmuş Y1 - 2018 PY - 2018 N1 - DO - T2 - Düzce Üniversitesi Bilim ve Teknoloji Dergisi JF - Journal JO - JOR SP - 962 EP - 982 VL - 6 IS - 4 SN - -2148-2446 M3 - UR - Y2 - 2018 ER -
EndNote %0 Düzce Üniversitesi Bilim ve Teknoloji Dergisi Image Denoising with Modified Grey Wolf Optimizer %A Hüseyin Avni Ardaç , Pakize Erdoğmuş %T Image Denoising with Modified Grey Wolf Optimizer %D 2018 %J Düzce Üniversitesi Bilim ve Teknoloji Dergisi %P -2148-2446 %V 6 %N 4 %R %U
ISNAD Ardaç, Hüseyin Avni , Erdoğmuş, Pakize . "Düzenlenmiş Gri Kurt Optimizasyon Algoritması ile Gürültü Temizleme". Düzce Üniversitesi Bilim ve Teknoloji Dergisi 6 / 4 (Ağustos 2018): 962-982.