Contrast Enhancement Using Optimal Threshold Histogram Equalization

Abstract: Image enhancement is one of the challenging issues in image processing concept. Contrast enhancement techniques are used for improving visual quality of low contrast images. Contrast enhancement plays a fundamental role in image/video processing. Histogram Equalization (HE) is one of the most commonly used methods for image contrast enhancement. However, HE and most other contrast enhancement methods may produce unnatural looking images. The images obtained by these methods are not suitable to use in applications such as consumer electronic products where brightness preservation is necessary to avoid annoying artifacts. To solve such problems, we proposed a novel and efficient contrast enhancement method based on genetic algorithm in this paper. This algorithm is fast and very less time consuming as compared to other techniques such as global histogram equalization by taking CDF and finding out the transfer function. Here in our work we are going to enhance images using histogram equalization of images by reconfiguring their pixel spacing using optimization through GA (Genetic algorithm). We will get more optimized results with the use of GA with respect to other optimization techniques.

Keywords: Contrast Enhancement, Foreground Enhancement, Genetic Algorithm, Histogram Equalization, Cumulative Density Function.