DIFFERENT IMAGE FUSION ALGORITHMS and SPOT 5 Data

Year 2010, Issue: 101, 0 - 0, 01.02.2010

Filiz Bektaş Balçık Çiğdem Göksel

Abstract

Image fusion term includes multiple techniques used to combine the detail of a high-resolution panchromatic image and the color information of a low-resolution multispectral image to producea a new image with the highest spatial resolution available in within the data set. The main objective of image fusion of multi resolution data is to preserve maximum spectral information quality from the MS data while increasing the spatial resolution by producing new images with enhanced interpretability. The fusion method used should not deteriorate and distroy the spectral characteristics of the MS data. Objects, which are spectrally separable in the original data, must be still separable in the fused data. There are many advantages of using fused data such as visual interpretation improvement, derivation of more accurate and reliable data for change detection and classification analysis. In this study, IHS, Multiplicative, Brovey, PCA and High Pass Filter fusion methods were used to fuse SPOT 5 MS and SPOT 5 PAN data. Results were compared by using quantitative and qualitative methods.

Keywords

Remote Sensing, Image Processing, Environment, Image Fusion, SPOT 5

SPOT 5 ve Farklı Görüntü Birleştirme Algoritmaları

Abstract

Görüntü birleştirme terimi ile genellikle, yüksek mekansal çözünürlüklü tek bantlı Pankromatik- PAN görüntünün, yüksek spektral çözünürlüklü fakat düşük mekansal çözünürlüklü çok bantlı Multispectral-MS görüntü ile veri kalitesinin arttırılması için birleştirilmesi tanımlanmaktadır. Elde edilen sonuç görüntüler maksimum mekansal çözünürlüğe ve kaliteli spektral bilgiye sahip olmaktadır. Uygulanan algoritmaların spektral özellikleri tahrip etmemesi gerekmektedir. Yöntemin kullanılmasının, görüntünün görsel yorumlanmasının arttırılması, görüntüden değişim tespiti ve sınıflandırma için doğru bilgi çıkarımı gibi avantajları bulunmaktadır. Bu çalışmada, SPOT 5 MS ve SPOT 5 PAN görüntülerinin birleştirilmesi için IHS, Brovey, Multiplicative, HPF ve PCA görüntü birleştirme yöntemleri uygulanmış ve elde edilen sonuçlar görsel ve istatistik açıdan karşılaştırılmıştır.

Keywords

Uzaktan algılama, Görüntü İşleme, Çevre, görüntü birleştirme, SPOT 5

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