Contrast Image Enhancement Based on Cloud Adaptive Particle Swarm Algorithm
Shao Ming-sheng · Video Engineering · 2013
According to the contrast image enhancement algorithms,adaptive cloud particle swarm algorithm is used.First of all,the cloud model produces cloud droplets,and determines cloud characteristic value.Then normal cloud generator generates particles based on the particle individual fitness,the population is divided into three cloud groups and used different inertia weight adjustment strategy,adaptive operator so that the weight with the particle′s fitness decreases,thereby realizing a particle made the smaller weight,in the largest fitness is not absolute zero,thereby improving the avoid local optimum capacity.Finally,angiography images by logarithmic gray transform enhancement,to seek the best parameter combination is transformed into the problem of adaptive cloud particle swarm optimization problem.The experimental simulation results show that,in the cloud membership of local image pixel gray region is relatively concentrated,with clear edge enhancement effect.