Application of Particle Swarm Optimization in Histogram Equalization for image enhancement

The basic and most common technique for contrast adjustment in the image is using Histogram Equalization (HE). It is based on equalizing the histogram of the image and subsequently enhancing its contrast, and results in overall contrast improvement. This paper introduces a combination of normal HE technique and Particle Swarm Optimization (PSO) algorithm for enhancing distorted image naturally. The process is as follows. The image is separated into red, green and blue (RGB) channels and PSO algorithm is applied into each channel in order to get its best fitness value. The fitness value that is obtained then will be applied into HE´s normalization, after that the processed color image will be merged back to RGB image. Experimental results have shown the effectiveness in improving the contrast of the original images without introducing disturbing artifacts caused by normal HE.