Adaptive Image Enhancement Based on Particle Swarm Optimization with Contracted Range of Velocity

Based on the analysis of inertia weightω and the maximal flying speed Vm ax,the improved Particle Swarm Optimization with Contracted range of search Velocity(CV-PSO) is proposed for the adaptive image enhancement.It combines with incomplete Beta operator which containes all different kinds of typical transformation functions.The algorithm is used for the basic and traffic images enhancement.It compares its performance with that of basic Particle Swarm Optimization(PSO) and other improved PSO.Results show that CV-PSO is effective and superior.Moreover,it is better than traditional histogram equalization method in visual quality.