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Satellite images usually contain narrow brightness level. This enables the need for enhancing these images but the important details need to be retained without loss of information. Image enhancement techniques can be broadly classified as: spatial and frequency domain techniques. Histogram Equalization is one of the prominent image enhancement techniques which can be applied to a whole image or some extracted part in an image. It is used to improve the overall visual appearance of the image. Various metaheuristic based algorithms are in trend today. Particle Swarm Optimization (PSO) is one such algorithm which is used for image enhancement. Some classical evolutionary computation algorithms are also being used for image enhancement. Another proposed method to enhance the contrast of a gray-level image was done using Genetic Algorithm (GA) which measures the fitness of an individual. This is done by finding the intensity of spatial edges in the image. Another prominent method is using the transformation functions to produce an enhanced image by GA. This method seems to perform fairly well to enhance the image. But the GA and PSO method suffer from the limitation that they get trapped in local minima.