title: Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization.
abstract: Image enhancement methods have been widely used to improve the visual effects of images. Owing to its simplicity and effectiveness histogram equalization (HE) is one of the methods used for enhancing image contrast. However, HE may result in over-enhancement and feature loss problems that lead to unnatural look and loss of details in the processed images. Researchers have proposed various HE-based methods to solve the over-enhancement problem; however, they have largely ignored the feature loss problem. Therefore, a contrast enhancement algorithm based on gap adjustment for histogram equalization (CegaHE) is proposed. It refers to a visual contrast enhancement algorithm based on histogram equalization (VCEA), which generates visually pleasing enhanced images, and improves the enhancement effects of VCEA. CegaHE adjusts the gaps between two gray values based on the adjustment equation, which takes the properties of human visual perception into consideration, to solve the over-enhancement problem. Besides, it also alleviates the feature loss problem and further enhances the textures in the dark regions of the images to improve the quality of the processed images for human visual perception. Experimental results demonstrate that CegaHE is a reliable method for contrast enhancement and that it significantly outperforms VCEA and other methods.
authors.affiliation: Department of Electrical and Electronic Engineering, Chung Cheng Institute of Technology, National Defense University, Taoyuan 33551, Taiwan. davidchiu@ndu.edu.tw.
authors.forename: Chung-Cheng
authors.initials: CC
authors.lastname: Chiu
authors.affiliation: School of Defense Science, Chung Cheng Institute of Technology, National Defense University, Taoyuan 33551, Taiwan. chihchungting@gmail.com.
authors.forename: Chih-Chung
authors.initials: CC
authors.lastname: Ting
keywords: contrast enhancement; cumulative distribution function (CDF); gap adjustment; histogram equalization (HE); human visual perception