基于暗原色与逆暗原色融合的含明亮区域图像去雾

龚昌来; 罗聪; 申志强

doi:10.3788/YJYXS20163108.0831

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基于暗原色与逆暗原色融合的含明亮区域图像去雾

驱动与控制 | 更新时间：2020-07-07

- 基于暗原色与逆暗原色融合的含明亮区域图像去雾
- Haze removal algorithm for image with bright region based on dark channel and inverse dark channel fusion
- 液晶与显示 2016年31卷第8期页码：831-839
- 作者机构：
  
  1.嘉应学院电子信息工程学院, 广东梅州 514015
  2.解放军96311部队, 湖南靖州 418400
- 作者简介：
  
  龚昌来(1962-), 男, 湖南浏阳人, 教授, 主要从事图像与信号处理方面的研究。E-mail:dzxgcl@sohu.com
- 基金信息：
  
  广东省自然科学基金资助项目(S2012010010368);Natural Science Foundation of Guangdong Province of China(S2012010010368)
- DOI：10.3788/YJYXS20163108.0831
  中图分类号： TP391
- 收稿日期：2016-03-30，
  
  录用日期：2016-5-11，
  
  纸质出版日期：2016-08
- 稿件说明：
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龚昌来, 罗聪, 申志强. 基于暗原色与逆暗原色融合的含明亮区域图像去雾[J]. 液晶与显示, 2016,31(8):831-839.

Chang-lai GONG, Cong LUO, Zhi-qiang SHEN. Haze removal algorithm for image with bright region based on dark channel and inverse dark channel fusion[J]. Chinese journal of liquid crystals and displays, 2016, 31(8): 831-839.
龚昌来, 罗聪, 申志强. 基于暗原色与逆暗原色融合的含明亮区域图像去雾[J]. 液晶与显示, 2016,31(8):831-839. DOI： 10.3788/YJYXS20163108.0831.

Chang-lai GONG, Cong LUO, Zhi-qiang SHEN. Haze removal algorithm for image with bright region based on dark channel and inverse dark channel fusion[J]. Chinese journal of liquid crystals and displays, 2016, 31(8): 831-839. DOI： 10.3788/YJYXS20163108.0831.

摘要

针对暗原色先验模型对于图像明亮区域不适应，暗原色估计偏大，导致透射率估计偏小，出现色彩失真现象，本文介绍一种新的暗原色修正方法。提出一种逆暗原色概念，将雾化图像的暗原色与逆暗原色进行融合处理得到一种新的修正暗原色，从而获得比较真实的明亮区域透射率，有效消除了明亮区域的色彩失真。以有效细节强度、色调还原程度、结构信息及综合测评作为图像质量评价指标，与目前流行算法进行对比实验，本文算法的色调还原程度指标平均值提高41.1%，综合测评指标平均值提高48.7%。实验结果表明，本文算法在改善明亮区域色彩失真及提高去雾图像总体质量方面优于目前流行算法。

Abstract

Aiming at the problem that dark channel prior model does not suit the image bright region

since dark channel estimate is too small

the estimated transmittance is small

and color distortion occurs

a new method for correcting dark channel has been proposed. One kind of inverse dark channel concepts have been proposed

dark channel and inverse dark channel of the haze image are fused to get a new dark channel

thereby obtaining more real bright area transmittance

effectively eliminating color distortion in the bright region. Effective strength of the details

the degree of reduction of tone

structure information and comprehensive evaluation as the image quality evaluation index

compared with the current popular algorithms

the average value of tonal reproduction degree is improved by 41.1% and the average comprehensive evaluation is increased by 48.7%. Experimental results show that proposed method is superior to the current popular algorithms in improving the color distortion of the bright region and improving the overall quality of the image haze removal.

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references

郭璠, 蔡自兴, 谢斌, 等.图像去雾技术研究综述与展望[J].计算机应用, 2010, 30(9):2417-2421.

GUO F, CAI Z X, XIE B, et al. Review and prospect of image dehazing techniques[J]. Journal of Computer Applications, 2010, 30(9): 2417-2421. (in Chinese)

李滚, 吴劼夫, 雷志勇.图像雾霾等级评价及去雾技术研究进展[J].激光杂志, 2014, 35(9):1-6.

LI G, WU J F, LEI Z Y. Research progress of image haze grade evaluation and dehazing technology[J].Laser Journal, 2014, 35(9): 1-6. (in Chinese)

HE K M, SUN J, TANG X O. Single image haze removal using dark channel prior[C]. Proceedings of the 27th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, Miami: IEEE, 2009: 1956-1963.

ANCUTI C O, ANCUTI C, HERMANS C, et al. A fast semi-inverse approach to detect and remove the haze from a single image[C]. Proceedings of the 10th Asian Conference on Computer Vision, Queenstown, New Zealand: Springer, 2010: 501-514.

南栋, 毕笃彦, 马时平, 等.基于景深约束的单幅雾天图像去雾算法[J].电子学报, 2015, 43(3):500-504.

NAN D, BI D Y, MA S P, et al. Single image dehazing method based on scene depth constraint[J]. Acta Electronica Sinica, 2015, 43(3): 500-504. (in Chinese)

李加元, 胡庆武, 艾明耀, 等.结合天空识别和暗通道原理的图像去雾[J].中国图象图形学报, 2015, 20(4):514-519.

LI J U, HU Q W, AI M Y, et al. Image haze removal based on sky region detection and dark channel prior[J]. Journal of Image and Graphics, 2015, 20(4): 514-519. (in Chinese)

雷琴, 施朝健, 陈婷婷.基于天空区域分割的单幅海面图像去雾方法[J].计算机工程, 2015, 41(5):237-242.

LEI Q, SHI C J, CHEN T T. Single sea image haze removal method based on segmentation of sky area[J]. Computer Engineering, 2015, 41(5): 237-242. (in Chinese)

WANG G Y, REN G H, JIANG L H, et al. Single image dehazing algorithm based on sky region segmentation[J]. Information Technology Journal, 2013, 12(6): 1168-1175.

蒋建国, 侯天峰, 齐美彬.改进的基于暗原色先验的图像去雾算法[J].电路与系统学报, 2011, 16(2):7-12.

JIANG J G, HOU T F, QI M B. Improved algorithm on image haze removal using dark channel prior[J].Journal of Circuits and Systems, 2011, 16(2): 7-12. (in Chinese)

孙小明, 孙俊喜, 赵立荣, 等.暗原色先验单幅图像去雾改进算法[J].中国图象图形学报, 2014, 19(3):381-385.

SUN X M, SUN J X, ZHAO L R, et al. Improved algorithm for single image haze removing using dark channel prior[J]. Journal of Image and Graphics, 2014, 19(3): 381-385. (in Chinese)

张登银, 鞠铭烨, 王雪梅.一种基于暗通道先验的快速图像去雾算法[J].电子学报, 2015, 43(7):1437-1443.

ZHANG D Y, JU M Y, WANG X M. A fast image daze removal algorithm using dark channel prior[J].Acta Electronica Sinica, 2015, 43(7): 1437-1443. (in Chinese)

NARASIMHAN S G, NAYAR S K. Contrast restoration of weather degraded images[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(6): 713-724.

高银, 云利军, 石俊生, 等.基于各向异性高斯滤波的暗原色理论雾天彩色图像增强算法[J].计算机辅助设计与图形学学报, 2015, 27(9):1701-1706.

GAO Y, YUN L J, SHI J S, et al. Enhancement dark channel algorithm of color fog image based on the anisotropic Gaussian filtering[J]. Journal of Computer-Aided Design & Computer Graphics, 2015, 27(9): 1701-1706. (in Chinese)

王卫星, 肖翔, 陈良琴.结合最小滤波和引导滤波的暗原色去雾[J].光学精密工程, 2015, 23(7):2100-2108.

WANG W X, XIAO X, CHEN L Q. Image dark channel prior haze removal based on minimum filtering and guided filtering[J].Optics and Precision Engineering, 2015, 23(7): 2100-2108. (in Chinese)

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.

李大鹏, 禹晶, 肖创柏.图像去雾的无参考客观质量评测方法[J].中国图象图形学报, 2011, 16(9):1753-1757.

LI D P, YU J, XIAO C B. No-reference quality assessment method for defogged images[J].Journal of Image and Graphics, 2011, 16(9): 1753-1757. (in Chinese)

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