| 一种光照条件自判断的夜间灰度图像增强算法 |
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| 引用本文： | 王玺琨,刘艳,张清祎,张巧珍,张相芬. 一种光照条件自判断的夜间灰度图像增强算法[J]. 上海师范大学学报(自然科学版), 2021, 50(1): 101-107 |
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| 作者姓名： | 王玺琨 刘艳 张清祎 张巧珍 张相芬 |
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| 作者单位： | 上海师范大学信息与机电工程学院,上海201418;上海师范大学信息与机电工程学院,上海201418;上海师范大学信息与机电工程学院,上海201418;上海师范大学信息与机电工程学院,上海201418;上海师范大学信息与机电工程学院,上海201418 |
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| 基金项目： | 国家自然科学基金（61862029；11904233） |
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| 摘 要： | 借鉴双直方图均衡(BBHE)和图像分割的思想,对夜间灰度图像进行光照条件自判断的增强研究,对光照条件较好、光照条件较差和光照条件较差但存在少数极亮区域的图像分别采用不同的方法进行增强处理.实验结果表明:所提算法可以突出夜间灰度图像暗处的细节,增大图像的对比度,并有效解决增强后图像整体亮度过高的问题,具有较强的普适性.
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| 关 键 词： | 夜间图像 图像分割 双直方图均衡(BBHE) 最大类间方差 限制对比度自适应直方图均衡 |
| 收稿时间： | 2020-12-09 |
A night gray image enhancement algorithm based on self-judgment of illumination conditions |
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| WANG Xikun,LIU Yan,ZHANG Qingyi,ZHANG Qiaozhen and ZHANG Xiangfen. A night gray image enhancement algorithm based on self-judgment of illumination conditions[J]. Journal of Shanghai Normal University(Natural Sciences), 2021, 50(1): 101-107 |
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| Authors: | WANG Xikun LIU Yan ZHANG Qingyi ZHANG Qiaozhen ZHANG Xiangfen |
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| Affiliation: | College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, China,College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, China,College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, China,College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, China and College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, China |
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| Abstract: | In this paper, the theory of brightness preserving Bi-histogram equalization(BBHE)and image segmentation were taken into account to enhance the night gray image by illumination condition self-judgment. Different methods were used to enhance the image under good illumination condition, poor illumination condition and poor illumination condition with few extremely bright areas respectively. The experimental results showed that the proposed algorithm was able to highlight the details of the dark places of the night gray image, which increased the contrast of the image, and effectively solved the problem that the overall brightness of the enhanced image was too high and had widespread popularity. |
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| Keywords: | night image image segmentation Bi-histogram equalization(BBHE) maximum interclass variance limit contrast adaptive histogram equalization |
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