EARTH OBSERVATION AND SATELLITE IMAGERY USING SPIDER MONKEY OPTIMIZATION (SMO)

Abstract

Remote Sensing Image classification is one of the major research areas due to its wide spectrum of applications including natural terrain feature classification, land use monitoring, ground water exploration, environmental disaster assessment and urban planning etc.Various Swarm Intelligence Techniques, nature inspired and some other intelligent techniques have been used in the field of remote sensing image classification. The various Artificial Intelligent techniques used in the area are Genetic Algorithm, Particle Swarm Optimization (PSO), Artificial Bee Colony optimization (ABC), Ant Colony Optimization (ACO), Cuckoo Search (CS) and also hybrid techniques of these for image classification& they also provide accuracy. An extensive research has been done in this field to classify various features of the image. Throughout feature extractions efforts can be made in direction of identifying all these features and classify the remote image areas consisting of, to get more efficiency than existing methods by means of spider monkey optimization a recent artificial intelligence technique. We used Artificial Intelligence Techniques in image classification of Natural Terrain features & using Spider Monkey Optimization (SMO) for Image Classification