Comparative Study of Soft Computing Based High-Resolution Satellite Image Segmentation in Additive and User-Oriented Color Space

Abstract

The satellite image is an assortment of the massive quantity of information for agriculture, environmental assessment and monitoring, mapping, military, and future planning of maintaining the natural resources and disasters. So it contains more useful and necessary information for analysis and processing. High resolution, low-cost, and easy availability of satellite images are the reasons for the fast growth in the usage of satellite images to extract the necessary information. For this aspect, various approaches have been proposed. Both soft and non-soft computing methods have been applied on satellite images to obtain meaningful clusters. Even though many kinds of literature are available for non-soft computing methods, only a limited number of authors have proposed soft computing based segmentation of satellite images. This work proposed a novel technique for the segmentation of RGB and HSI color space transformed satellite images using soft computing techniques.