Image Fusion with Metaheuristic Cuckoo Search Algorithm

Year 2020, Volume: 1 Issue: 1, 1 - 12, 31.03.2020

Volkan Yılmaz

Abstract

Component substitution-based fusion methods are among the most widespread image fusion methods in the literature. Despite the fact that these methods are very successful in enhancing the spatial detail quality, they tend to deteriorate the spectral quality of the input multispectral images. The main reason for this is that they are not so successful in optimizing the intensity component produced from the input multispectral bands. In this study, an image fusion method which utilizes metaheuristic cuckoo search algorithm was proposed to optimize the intensity component used in fusion process. The proposed method was applied on the Gram-Schmidt (GS) method, one of the most widely-used component substitution-based image fusion methods. The colour preservation performance of the proposed method was qualitatively and quantitatively compared not only against that of the High-Pass Filtering (HPF) method, but also against those of popular component substitution-based methods Multiplicative (MCV), Brovey (BRV), Principal Component Analysis (PCA), Ehlers (EHL), Modified Intensity-Hue-Saturation (MIHS), Synthetic Variable Ratio (SVR) and original GS in two test sites. The results showed that the proposed method was successful in optimizing the intensity component and therefore preserved the colour content of the input multispectral image more successfully than other methods used.

Keywords

Image fusion, Metaheuristic optimization, Gram-Schmidt, Cuckoo search algorithm, Pansharpening, Component substitution-based image fusion

Metasezgisel Guguk Kuşu Arama Algoritması ile Görüntü Kaynaştırma

Abstract

Bileşen değişimi tabanlı görüntü kaynaştırma yöntemleri literatürde en fazla kullanılan görüntü kaynaştırma yöntemleri arasındadır. Bu yöntemler konumsal detayları iyileştirmedeki başarılarına rağmen girdi çok bantlı görüntülerin renk yapısını bozma eğilimindedirler. Bu durumun temel nedeni bu yöntemlerin girdi çok bantlı görüntülerin bantlarından elde ettikleri yoğunluk bileşenini optimize edememeleridir. Bu çalışmada, yoğunluk bileşeninin optimize edilebilmesi için metasezgisel guguk kuşu arama algoritmasından yararlanan bir görüntü kaynaştırma yöntemi önerilmiştir. Önerilen yaklaşım en yaygın kullanılan bileşen değişimi tabanlı kaynaştırma yöntemlerinden biri olan Gram-Schmidt (GS) yöntemi üzerinde uygulanmıştır. Önerilen yöntemin renk koruma performansı Yüksek Geçirgen Filtreleme (HPF) yönteminin yanı sıra popüler bileşen değişimi tabanlı yöntemlerden olan Multiplicative (MCV), Brovey (BRV), Temel Bileşenler Analizi (PCA), Ehlers (EHL), Modifiye edilmiş Intensity-Hue-Saturation (MIHS), Synthetic Variable Ratio (SVR) ve orijinal GS yöntemlerinin renk koruma performansları ile iki test bölgesinde niteliksel ve niceliksel olarak karşılaştırılmıştır. Elde edilen sonuçlar önerilen yöntemin yoğunluk bileşenini başarılı bir şekilde optimize ettiğini ve bu nedenle de girdi çok bantlı görüntünün renk içeriğini kullanılan diğer yöntemlere oranla daha başarılı bir şekilde koruduğunu göstermiştir.

Keywords

Görüntü kaynaştırma, Metasezgisel optimizasyon, Gram-Schmidt, Guguk kuşu arama algoritması, Pankromatik keskinleştirme, Bileşen değişimi tabanlı görüntü kaynaştırma

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