Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization
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 un...
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doaj-3af42919bb3a47ec990b5010969a93bd2020-11-25T02:48:02ZengMDPI AGSensors1424-82202016-06-0116693610.3390/s16060936s16060936Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram EqualizationChung-Cheng Chiu0Chih-Chung Ting1Department of Electrical and Electronic Engineering, Chung Cheng Institute of Technology, National Defense University, Taoyuan 33551, TaiwanSchool of Defense Science, Chung Cheng Institute of Technology, National Defense University, Taoyuan 33551, TaiwanImage 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.http://www.mdpi.com/1424-8220/16/6/936cumulative distribution function (CDF)contrast enhancementhistogram equalization (HE)human visual perceptiongap adjustment |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chung-Cheng Chiu Chih-Chung Ting |
spellingShingle |
Chung-Cheng Chiu Chih-Chung Ting Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization Sensors cumulative distribution function (CDF) contrast enhancement histogram equalization (HE) human visual perception gap adjustment |
author_facet |
Chung-Cheng Chiu Chih-Chung Ting |
author_sort |
Chung-Cheng Chiu |
title |
Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization |
title_short |
Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization |
title_full |
Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization |
title_fullStr |
Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization |
title_full_unstemmed |
Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization |
title_sort |
contrast enhancement algorithm based on gap adjustment for histogram equalization |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2016-06-01 |
description |
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. |
topic |
cumulative distribution function (CDF) contrast enhancement histogram equalization (HE) human visual perception gap adjustment |
url |
http://www.mdpi.com/1424-8220/16/6/936 |
work_keys_str_mv |
AT chungchengchiu contrastenhancementalgorithmbasedongapadjustmentforhistogramequalization AT chihchungting contrastenhancementalgorithmbasedongapadjustmentforhistogramequalization |
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