Low Contrast Color Image Enhancement Using Particle Swarm Optimization

In this paper, we represent a new optimal simplified approach for image enhancement of low contrast color images using adaptive contrast enhancement and particle swarm optimization (PSO). The HSV (hue, saturation and value) color space is used for the enhancement process. In order to preserve the original color of the image, hue component is kept same. The intensity component is enhanced using the unsharp masking technique. A new contrast gain is defined for amplification of the unsharp mask for producing an enhanced image. The saturation component is enhanced using the power-law transformation. A new objective function comprising entropy, image exposure, histogram flatness and histogram spread is introduced and optimized using PSO to learn the parameters used for the enhancement of a given image. The proposed approach is evaluated using different low contrast test images. Different performance measures are used for the quantitative analysis of the proposed approach.