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International Journal of Computer Science and Informatics

Abstract

A novel supervised classification approach is proposed for high-resolution dual-polarization (dual-pol) amplitude COSMO SkyMed images. Coherence, mean backscattering coefficient and backscatter difference images are generated, from which the False Color Composite (FCC) image is formed. A classification scheme based on maximum likelihood algorithm land cover classification is implemented on the false color composite image to classify the river, vegetation and the urban areas of Jharia, located in the state of Jharkhand in India using MATLAB 7.6 and ENVI 4.7.

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