Optimization Color Quantization in L * A * B * Color Space Using Particle Swarm Optimization

Color quantization is a process that reduces the distinct colors used in an image. The main objective of quantization should be such that it must not cause the loss of visual information from the image but reduces its memory requirements. In this paper the color quantization in LAB color space using PSO is done. Particle swarm optimization (PSO) is an evolutionary computation technique developed through a simulation of simplified social models. PSO is based on swarms such as fish schooling and bird flocking. [2].The LAB color model based clustering is used. In our present work first of all we will find the color image which is to be quantized. Then color map will be created where a small set of colors is chosen from all possible combination in Lab color space. Then the proposed algorithm will be applied to get the optimized solution. Keywords— Color quantization, lab color space clustering, particle swarm optimization.