Abstract
Natural Computing techniques are becoming popular these days because of their features like adaptation, avoiding local optima, finding optimal solutions etc. These can be broadly categorized as inspired from human mind and swarm intelligence. Natural computing algorithms are used in every field of research as these are powerful, has very low implementation cost, can be used to solve nonlinear problems and have optimization capability to solve a very big problems. Satellite image Classification is one of the applications where these Computational algorithms are used to provide good accuracy. Hyper spectral images are very high in dimensions need such type of algorithms that can optimize the solutions in less time. This paper has analyzed various natural computing techniques to optimize the solutions which ultimately help in increasing the classification accuracy of very high dimensional hyper spectral satellite images.
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