Color Image Enhancement Using Steady State Genetic Algorithm

The purpose of this paper is to enhance the colored images using the enhancement developed steady state genetic algorithm, SSGA, with modified fitness function to get more accurate result and less noise. In this paper the Hue Saturation Intensity (HSV) color model will be used, after enhance the S, H and V components the transformation will be made to RGB color model. We have developed three models for enhancing the colorful and chromaity of the image with different types of input - output and different type of parameter. The models are compared based on their ability to train with lowest error values. To use these models the input RGB color image is converted to an intensity image using Space Variant Luminance Map SVLM.