一种改进的雾天监控图像增强算法

大气与环境光学学报 ›› 2018, Vol. 13 ›› Issue (4): 309-314.

一种改进的雾天监控图像增强算法

王振东1, 江巨浪1*, 马宏亮1, 程刚2

（1 安庆师范大学物理与电气工程学院, 安徽安庆 246133；
2 安徽理工大学机械工程学院, 安徽淮南 232001）

收稿日期:2017-08-22 修回日期:2017-09-07 出版日期:2018-07-28 发布日期:2018-07-10
通讯作者: 江巨浪 (1967-), 男,安徽潜山人,博士,教授,主要从事图形图像处理方面的研究。 E-mail:jiangjulang1@126.com
作者简介:王振东 (1992-), 男,安徽枞阳人,硕士,主要从事图形图像处理方面的研究。
基金资助:
Supported by National Natural Science Foundation of China(国家自然科学基金, 11604002, 51607004)

An Improved Enhancement Algorithm of Fog Surveillance Image

WANG Zhendong1, JIANG Julang1*, MA Hongliang1, CHENG Gang2

( 1 School of Physics and Electrical Engineering, Anqing Normal University, Anqing 246133, China;
2 College of Mechanical Engineering, Anhui University of Science & Technology, Huainan 232001, China)

Received:2017-08-22 Revised:2017-09-07 Published:2018-07-28 Online:2018-07-10
Contact: 江巨浪 (1967-), 男,安徽潜山人,博士,教授,主要从事图形图像处理方面的研究。 E-mail:jiangjulang1@126.com
About author:王振东 (1992-), 男,安徽枞阳人,硕士,主要从事图形图像处理方面的研究。
Supported by:
Supported by National Natural Science Foundation of China(国家自然科学基金, 11604002, 51607004)

摘要/Abstract

摘要：

视频监控或激光成像在大气环境监测中有着广泛应用，然而在雾天条件下获取的图像不可避免存在视觉质量降低问题。针对雾天图像对比度增强以及噪声抑制的需要，提出了一种改进的雾天图像增强算法。首先对原图像进行正反双向的双直方图均衡处理与融合，然后重复采用上述方法对融合图像的小波分解低频系数矩阵进行增强处理，最后将处理结果和高频系数矩阵进行小波重构得到输出图像。实验结果表明，该算法处理雾天监控图像能够取得较好的对比度增强与噪声抑制性能。

关键词: 图像增强, 直方图均衡, 雾天监控图像, 小波域

Abstract:

Video surveillance or laser imaging is widely used in atmospheric environment monitoring, but the image quality is inevitably reduced in fog weather. In order to meet the need of contrast enhancement and noise suppression in foggy image, an improved image enhancement algorithm for foggy image is proposed. Firstly, the original image is enhanced by bidirectional histogram equalization processing and fusion. Then the same method is used to deal with the low-frequency coefficient matrix which obtained by wavelet decomposition of the last fused image. Finally the output image can be obtained by wavelet reconstruction of the processing result and the high frequency coefficient matrix. Experimental results show that the proposed algorithm can achieve better contrast enhancement and noise suppression performance in fog surveillance images.

Key words: image enhancement, histogram equalization, fog surveillance image, wavelet domain

中图分类号:

TP391.41

王振东江巨浪马宏亮程刚. 一种改进的雾天监控图像增强算法[J]. 大气与环境光学学报, 2018, 13(4): 309-314.

WANG Zhen-Dong, JIANG Ju-Lang, MA Hong-Liang, CHENG Gang. An Improved Enhancement Algorithm of Fog Surveillance Image[J]. Journal of Atmospheric and Environmental Optics, 2018, 13(4): 309-314.

参考文献

[1] Gonzalez R C, Woods R E. Digital Image Processing [M]. 3rd ed. Transl. by Ruan Qiuqi. Beijing: Publishing House of Electronics Industry, 2011: 72-88.
Gonzalez R C, Woods R E. 数字图像处理 [M]. 第三版. 阮秋琦, 译. 北京:电子工业出版社, 2011: 72-88.
[2] Dai Shubo, Xu Wei, Piao Yongjie, et al. Remote sensing defogging based on dark channel prior [J]. Acta Electronica Sinica, 2017, 37(3): 348-354(in Chinese).
代书博, 徐伟, 朴永杰, 等. 基于暗原色先验的遥感图像去雾方法 [J].光学学报, 2017, 37(3): 348-354.
[3] Kim Y T. Enhancement using brightness preserving bi-histogram equalization [J]. IEEE Transactions on Consumer Electronics, 1997, 43(1): 1-8.
[4] Wang Y, Chen Q, Zhang B. Image enhancement based on equal area dualistic sub-image histogram equalization method [J]. IEEE Transactions on Consumer Electronics, 1999, 45(1): 68-75.
[5] Kim J Y, Kim L S, Hwang S H. An advanced contrast enhancement using partially overlapped sub -block histogram equalization [J]. IEEE Transactions on Circuits and Systems for Video Technique, 2001, 11(4): 475-484.
[6] Jiang Julang, Zhang Yousheng, Xue Feng, et al. Local histogram equalization with brightness preservation [J]. Acta Electronica Sinica, 2006, 34(5): 861-866(in Chinese).
江巨浪, 张佑生, 薛峰, 等. 保持图像亮度的局部直方图均衡算法 [J]. 电子学报, 2006, 34(5): 861-866.
[7] Zhang Yanhong, Hou Dewen. An image enhancement algorithm based on wavelet frequency division and bi-histogram equalization [J]. Computer Applications and Software, 2007, 107(122): 108-122(in Chinese).
张燕红, 侯德文. 基于小波分频和二次均衡的图像增强算法 [J]. 计算机应用与软件, 2007, 107(122): 108-122.
[8] Kong Lingjun, Nie Peng, Sun Yewei. Low contrast color image enhancement algorithm based on adaptive threshold [C]. Proceedings of the Fourth China Academic Conference on Printing and Packaging, 2015(in Chinese).
孔玲君, 聂鹏, 孙叶维. 基于自适应阈值的低对比度彩色图像增强算法 [C]. 第四届中国印刷与包装学术会议论文集, 2015.
[9] He K M, Sun J, Tang X O, et al. Single image haze removal using dark channel prior [C]. Processdings of the IEEE Conference on Computer Vision and Pattern recognition Miami:IEEE, 2009: 1956-1963.
[10] He K M, Sun J, Tang X O. Guided image filtering [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6): 1397-1409.
[11] Jiang J L, Wang Z D, Wu Z X, et al. Histogram equalization algorithm for color image based on wavelet domain and HSI color space [J]. Journal of Anqing Teachers College: Natural Science Edition, 2016, 22(2): 26-29(in Chinese).
江巨浪, 王振东, 伍兆祥, 等. HSI色彩空间的彩色图像小波域直方图均衡算法 [J]. 安庆师范学院: 自然科学版, 2016, 22(2): 26-29.