Landsat Uydu Görüntülerinde Derin Öğrenme Tabanlı Tek Görüntülü Süper-Çözünürlük Deneyleri

Yıl 2020, Cilt: 5 Sayı: 3, 194 - 204, 25.12.2020

Serdar Çiftçi , Muhittin Karaman

https://doi.org/10.46578/humder.819176

Cited By: 2

Öz

Halka açık sunulan uydu görüntülerinin çözünürlükleri genellikle düşüktür. Düşük çözünürlük bilgi kaybına yol açtığından uzaktan algılama alanında çalışılan problemin türüne bağlı olarak istenilen başarım sergilenemeyebilmektedir. Böyle bir durumda düşük çözünürlüklü görüntülerin yüksek çözünürlüklü hale getirilmesi için süper-çözünürlük algoritmaları kullanılır. Bu çalışmada derin öğrenme tabanlı hazır eğitilmiş EDSR ve DBPN modelleri kullanılmış ve sonuçlarının pan-keskinleştirmeye ne kadar yakın olduğu incelenmiştir. Yapılan deneyler sonucunda EDSR ve DBPN modelleriyle elde edilen görüntülerin görüntü işleme tabanlı Bicubic yöntemine nazaran daha keskin geçişli ama objektif değerlendirmede daha zayıf olduğu gözlenmiştir.

Anahtar Kelimeler

Süper-çözünürlük, EDSR, DBPN, Bicubic, Landsat-8, Pan-sharpenning

Kaynakça

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