Image Enhancement Using Hybrid Intelligent Optimization

Contrast enhancement plays an important role in image processing system, which is used to improve image quality or extract the fine details in degraded images. Image enhancement was regarded as an optimization problem and a kind of hybrid intelligent algorithm was proposed in this paper to optimize parameters of image enhancement operator who took the advantage of local gray distribution and the global statistical information of source image. Advantages of bacterial foraging algorithm and particle swarm optimization were combined into the Hybrid intelligent algorithm proposed in this paper, and the optimized fitness function was based on entropy and edge information of image. The results of simulation and experiment showed that after the application of this method not only the overall image contrast was enhanced but also details information of target image was effectively enriched, and noise amplification was restrained.