一种改进的容差机制图像去雾算法

龚昌来; 罗聪

doi:10.3788/YJYXS20163111.1098

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一种改进的容差机制图像去雾算法

显示与图像 | 更新时间：2020-08-12

- 一种改进的容差机制图像去雾算法
- Improved haze removal algorithm based on tolerance mechanism
- 液晶与显示 2016年31卷第11期页码：1098-1104
- 作者机构：
  
  嘉应学院电子信息工程学院, 广东梅州 514015
- 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/YJYXS20163111.1098
  中图分类号： TP391
- 收稿日期：2016-06-08，
  
  录用日期：2016-7-18，
  
  纸质出版日期：2016-11
- 稿件说明：
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龚昌来, 罗聪. 一种改进的容差机制图像去雾算法[J]. 液晶与显示, 2016,31(11):1098-1104.

Chang-lai GONG, Cong LUO. Improved haze removal algorithm based on tolerance mechanism[J]. Chinese journal of liquid crystals and displays, 2016, 31(11): 1098-1104.
龚昌来, 罗聪. 一种改进的容差机制图像去雾算法[J]. 液晶与显示, 2016,31(11):1098-1104. DOI： 10.3788/YJYXS20163111.1098.

Chang-lai GONG, Cong LUO. Improved haze removal algorithm based on tolerance mechanism[J]. Chinese journal of liquid crystals and displays, 2016, 31(11): 1098-1104. DOI： 10.3788/YJYXS20163111.1098.

摘要

针对经典容差机制图像去雾算法存在的对部分明亮区域透射率提升力度不够，难以彻底消除色彩失真问题，本文提出一种改进算法。将原算法中对明亮区域透射率根据容差进行双曲线提升修正变为线性提升修正，使透射率平稳提升，并适当增大了透射率提升力度，有效消除色彩失真。以方差和色调还原度作为图像去雾的客观质量评测指标，与暗原色先验算法和经典容差机制算法进行对比实验。实验结果表明，本文算法在改善明亮区域色彩失真及提高图像去雾效果方面优于对比算法。

Abstract

In view of the problem that exists in the classic tolerance mechanism image haze removal algorithm

the efforts to enhance the transmission of the bright region is not enough

it is difficult to completely eliminate the color distortion

an improved algorithm is proposed herein. For the bright region transmission

according to the tolerance

hyperbolic type enhancement is adopted in the original algorithm

while linear enhancement correction is used in this paper

which makes the transmission enhance steadily. The effort to enhance the transmission is appropriately increased

thus the color distortion is effectively eliminated. Variance and color reduction degree are used as objective quality evaluation index for image haze removal. Compared with the dark channel prior algorithm and the classic tolerance mechanism algorithm

the proposed algorithm is superior to the contrast algorithms in improving the color distortion of the bright region and improving the image haze removal.

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references

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)

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

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(3):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.

吴笑天,鲁剑锋,贺柏根,等. 雾天降质图像的快速复原[J]. 中国光学, 2013,6(6):892-899.

WU X T, LU J F, HE B G, et al. Fast restoration of haze-degraded image[J]. Chinese Optics , 2013, 6(6):892-899. (in Chinese)

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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