Year 2020, Volume 8 , Issue 4, Pages 2266 - 2288 2020-10-29

Görüntü İyileştirme için Sıralı Modifiyeli Yerçekimi Arama Algoritması
Sequentially Modified Gravitational Search Algorithm for Image Enhancement

Ferzan KATIRCIOĞLU [1] , Uğur GÜVENÇ [2]


Yerçekimi Arama Algoritması (GSA), kütlesi birbirine yakın olan nesnelerin hızlanma eğilimi özelliğini temel almakta olup, birbirine bağlı birçok parametre içermektedir. Bu parametreler arasındaki yerçekimi sabiti ajanların hızlarını ve konumlarını etkiler, yani arama kabiliyeti büyük ölçekli yerçekimi sabitine bağlıdır. Bu çalışmada, farklı zamanlarda iki operatörün kullanılması ve sırayla çalışmalarını kapsayan yeni algoritma önerilmiştir ve Sıralı Değiştirilmiş Yerçekimi Arama Algoritması (SMGSA) olarak adlandırılmıştır. SMGSA 10 temel ve 6 kompozit kıyaslama fonksiyonuna uygulanmaktadır. Her fonksiyon 30 kez çalıştırılır ve en iyi, ortalama ve medyan değerler elde edilmektedir. Elde edilen sonuçlar sezgisel optimizasyon algoritmaları arasında Genetik Algoritma (GA), Parçacık Sürüsü Optimizasyonu (PSO) ve GSA ile karşılaştırılmıştır. GSA ile operatör arasında her fonksiyon yakınsama hızı için standart sapma ve grafik karşılaştırmalar bulunmuştur. Bunun yanı sıra, Wilcoxon sıralama testi kullanılarak, verilerin ortalamalarının iki bağımlı GSA grubu ve yeni operatörler olarak karşılaştırılması gerçekleştirilmiştir. Ayrıca bu çalışmada, mühendislik uygulamalarından görüntü iyileştirme teknikleri arasında yer alan dönüşüm fonksiyonuna SMGSA uygulanmıştır. Bu yöntemin başarısı, kullanılan dönüştürme fonksiyonunun parametreleri optimize edilerek arttırılmıştır. Hem görsel hem de bilgi kalitesi açısından etkili bir gelişme sağlanmıştır.
Gravitational Search Algorithm (GSA) is based on the acceleration trend feature of objects with a mass towards each other and includes many interdependent parameters. The gravitational constant among these parameters influences the speeds and positions of the agents, meaning that the search capability depends on the largescale gravitational constant. The proposed new algorithm, which was obtained with the use of two operators at different times of the call and sequentially doing works, was named as Sequentially Modified ‎ Gravitational Search Algorithm (SMGSA). SMGSA is applied to 10 basic and 6 composite benchmark functions. Each function is run 30 times and the best, mean and median values are obtained. The achieved results are compared with the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and GSA among the heuristic optimization algorithms. Between GSA and the operator for each function convergence speed, standard deviation and graphical comparisons are included. Beside this, by using the Wilcoxon signed rank test, the comparison of the averages of the data as two dependent groups of GSA and the new operators is performed. It is seen that the obtained results provided better results than the other methods. Additionally, in this study, SMGSA was applied to the transformation function among image enhancement techniques which are engineering applications. The success of this method has been increased by optimizing the parameters of the transformation function used. Effective improvement has been achieved in terms of both visual and information quality.
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Primary Language en
Subjects Engineering
Journal Section Articles
Authors

Orcid: 0000-0001-5463-3792
Author: Ferzan KATIRCIOĞLU (Primary Author)
Institution: DÜZCE ÜNİVERSİTESİ
Country: Turkey


Orcid: 0000-0002-5193-7990
Author: Uğur GÜVENÇ
Institution: Duzce University
Country: Turkey


Dates

Publication Date : October 29, 2020

Bibtex @research article { dubited710153, journal = {Düzce Üniversitesi Bilim ve Teknoloji Dergisi}, issn = {}, eissn = {2148-2446}, address = {}, publisher = {Duzce University}, year = {2020}, volume = {8}, pages = {2266 - 2288}, doi = {10.29130/dubited.710153}, title = {Sequentially Modified Gravitational Search Algorithm for Image Enhancement}, key = {cite}, author = {Katırcıoğlu, Ferzan and Güvenç, Uğur} }
APA Katırcıoğlu, F , Güvenç, U . (2020). Sequentially Modified Gravitational Search Algorithm for Image Enhancement . Düzce Üniversitesi Bilim ve Teknoloji Dergisi , 8 (4) , 2266-2288 . DOI: 10.29130/dubited.710153
MLA Katırcıoğlu, F , Güvenç, U . "Sequentially Modified Gravitational Search Algorithm for Image Enhancement" . Düzce Üniversitesi Bilim ve Teknoloji Dergisi 8 (2020 ): 2266-2288 <https://dergipark.org.tr/en/pub/dubited/issue/57598/710153>
Chicago Katırcıoğlu, F , Güvenç, U . "Sequentially Modified Gravitational Search Algorithm for Image Enhancement". Düzce Üniversitesi Bilim ve Teknoloji Dergisi 8 (2020 ): 2266-2288
RIS TY - JOUR T1 - Sequentially Modified Gravitational Search Algorithm for Image Enhancement AU - Ferzan Katırcıoğlu , Uğur Güvenç Y1 - 2020 PY - 2020 N1 - doi: 10.29130/dubited.710153 DO - 10.29130/dubited.710153 T2 - Düzce Üniversitesi Bilim ve Teknoloji Dergisi JF - Journal JO - JOR SP - 2266 EP - 2288 VL - 8 IS - 4 SN - -2148-2446 M3 - doi: 10.29130/dubited.710153 UR - https://doi.org/10.29130/dubited.710153 Y2 - 2020 ER -
EndNote %0 Düzce Üniversitesi Bilim ve Teknoloji Dergisi Sequentially Modified Gravitational Search Algorithm for Image Enhancement %A Ferzan Katırcıoğlu , Uğur Güvenç %T Sequentially Modified Gravitational Search Algorithm for Image Enhancement %D 2020 %J Düzce Üniversitesi Bilim ve Teknoloji Dergisi %P -2148-2446 %V 8 %N 4 %R doi: 10.29130/dubited.710153 %U 10.29130/dubited.710153
ISNAD Katırcıoğlu, Ferzan , Güvenç, Uğur . "Sequentially Modified Gravitational Search Algorithm for Image Enhancement". Düzce Üniversitesi Bilim ve Teknoloji Dergisi 8 / 4 (October 2020): 2266-2288 . https://doi.org/10.29130/dubited.710153
AMA Katırcıoğlu F , Güvenç U . Sequentially Modified Gravitational Search Algorithm for Image Enhancement. DÜBİTED. 2020; 8(4): 2266-2288.
Vancouver Katırcıoğlu F , Güvenç U . Sequentially Modified Gravitational Search Algorithm for Image Enhancement. Düzce Üniversitesi Bilim ve Teknoloji Dergisi. 2020; 8(4): 2266-2288.
IEEE F. Katırcıoğlu and U. Güvenç , "Sequentially Modified Gravitational Search Algorithm for Image Enhancement", Düzce Üniversitesi Bilim ve Teknoloji Dergisi, vol. 8, no. 4, pp. 2266-2288, Oct. 2020, doi:10.29130/dubited.710153