The Best Spectral Merge Method for Panchromatic and Multi-Spectral Russian Canopus Satellite Images

Abstract

 Although nearly the whole Soviet Union satellite systems were developed for defense systems, many of them were developed slowly for civil applications. Later and during the Russian Union stage, many satellite systems were developed for both military and civil application. On the other hand, some of these satellites were developed for civil application specifically. During the stage between 2008 until 2015, the Russian Space Federal Program Accepted lunching three climate satellites (Elektro) and other two satellites (Arkon-2) for Radar earth surface scanning. During 2012 the satellites (Canopus, Zond-PP, BKA, Yubilebiny-2 (MIR), KVI) of civil applications were lunched. In General Organization of remote sensing in Syria, the Satellite Data Receiving Station receives satellite data from Canopus (KVI) Satellite, 2.1 spatial resolution Panchromatic (PAN) images and 10.5m spatial resolution four bands Multispectral (MS) images. In this paper, a 2.14m Pan and 10.50 m MS KVI satellite images that covered parts of Damascus country were used. After geometric correction of these satellite data using rectified Cartosat satellite image, five algorithms were evaluated for merging Pan and MS KVI satellite images. These algorithms were Principle Components, Multiplicative, Brovey Transform, High Pass Filter HPF, Wavelet. Using visual and statistical evaluation of the results of these five algorithms, results of HPF algorithm were the best.