Yüksek Çözünürlüklü Multispektral Uydu Görüntülerinde Kuvvetlendirilmiş Sınıflandırıcılar Kullanılarak Otomatik Yol Çıkarımı

Bu çalışmada yüksek çözünürlüklü multispektral uydu görüntülerinden karayolu çıkarımı için yeni bir yöntem önerilmiştir. Önerilen yöntem, literatürde genellikle su ve bitki örtüsünün sınıflandırılması için kullanılan ve spektral bantların oranlanmasıyla elde edilen indisler ile birlikte bölütleme sonuçları üzerinden elde edilen bölütlere ait yapısal özellikleri öznitelik olarak kullanmakta ve ADABOOST gözetimli bir öğrenme algoritmasını bu öznitelikler ile eğitmektedir. Algoritma çeşitli uydu görüntülerinde denenmiş, yol çıkarımında başarılı olduğu gözlemlenmiştir.

Anahtar Kelimeler:

Örüntü Tanıma, Uzaktan Algılama, Uydu Görüntüleri, Yol Çıkarımı

Road Extraction from Multispectral Satellite Images Using Boosted Classifiers

In this study, a new method for extracting road mask from high resolution multispectral satellite images is proposed. Proposed method uses indices which are generally utilized for water or vegetation detection in the literature with the structural properties of segments generated by segmentation procedure as features and trains ADABOOST supervised learning algorithm with them. The proposed method is tried on different satellite images and it is observed that the proposed method which is developed using Adaboost learning algorithm is succesful at extracting road networks from satellite images.

Keywords:

Pattern Recognition, Remote Sensing, Satellite Images, Road Extraction,

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