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Sensors 2016, 16(6), 936; doi:10.3390/s16060936

Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization

1
Department of Electrical and Electronic Engineering, Chung Cheng Institute of Technology, National Defense University, Taoyuan 33551, Taiwan
2
School of Defense Science, Chung Cheng Institute of Technology, National Defense University, Taoyuan 33551, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editor: Yael Nemirovsky
Received: 17 March 2016 / Revised: 25 May 2016 / Accepted: 16 June 2016 / Published: 22 June 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [12635 KB, uploaded 22 June 2016]   |  

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. View Full-Text
Keywords: cumulative distribution function (CDF); contrast enhancement; histogram equalization (HE); human visual perception; gap adjustment cumulative distribution function (CDF); contrast enhancement; histogram equalization (HE); human visual perception; gap adjustment
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Chiu, C.-C.; Ting, C.-C. Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization. Sensors 2016, 16, 936.

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