Abstract：In order to improve the effect of image dehazing, near and far scene dark channel prior, was proposed. Firstly,mixed dark channel prior was established, which is included minimum channel of near scene and dark channel prior of far scene, and set adjustment coefficient of different scene region. Secondly, atmosphere light value was estimated with 50 pixel color average value of mixed dark channel prior far scene, and added correction coefficient.Thirdly,transmission was optimizated with adaptive sliding window of guided filtering.Finally,process was given.Experiment simulation showed that mixed dark channel prior has better visual effect,and contrast ratio and visible edge contrast ratio of quantitative analysis indexes are better than other algorithms.
田源. 基于混合远景和近景区域暗通道算法的图像去雾研究[J]. 计量学报, 2019, 40(4): 583-588.
TIAN Yuan. Image Dehazing Based on Near and Far Scene Dark Channel Prior. Acta Metrologica Sinica, 2019, 40(4): 583-588.
［1］程磊,刘勇军.基于改进暗通道算法的图像去雾研究［J］. 计量学报,2019,40(2):220-224.
Cheng L,Liu Y J. Image Dehazing Based on Improved Dark Channel Prior Algorithm［J］. Acta Metrologica Sinica,2019,40(2):220-224.
［2］Tan R T. Visibility in bad weather from a single image［C］//IEEE. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Anchorage, AK, USA,2008: 1-8.
［3］Tarel J P, Hautiere N. Fast visibility restoration from a single color or gray level image［C］//IEEE Computer Society. Proceedings of the 2009 IEEE International Conference on Computer Vision. Washington, DC, USA,2009: 2201-2208.
［4］Fattal R. Single image dehazing［J］. ACM Transactions on Graphics, 2008, 27(3): 1-9.
［5］He K M, Sun J, Tang X O. Single image haze removal using dark channel prior［C］//IEEE Computer Society. Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition Workshops. Washington, DC, USA,2011: 1956-1963.
［6］曾接贤, 余永龙. 双边滤波与暗通道结合的图像保边去雾算法［J］. 中国图象图形学报, 2017, 22(2): 147-153.
Zeng J X, Yu Y L. Image defogging and edge preserving algorithm based on dark channel prior and bilateral filtering［J］. Journal of Image and Graphics, 2017, 22(2): 147-153.
［7］胡晨辉, 吕伟杰, 张飞. 导向滤波优化的单幅去雾算法［J］. 传感器与微系统, 2017, 36 (10): 129-132.
Hu C H, Lü W J, Zhang F. Algorithm for single image dehazing based on guided filtering optimization ［J］. Sensors and Microsystems, 2017, 36 (10): 129-132.
［8］姜德晶, 王树臣, 曾勇, 等. 分割映射的单幅彩色图像去雾方法［J］. 光电子·激光, 2017, 37(7): 780-787.
Jiang D J, Wang S C, Zeng Y, et al. Single color image dehazing method based on image segmentation ［J］. Journal of Optoelectronics ·laser, 2017, 37(7): 780-787.
［9］陈书贞, 任占广, 练秋生. 基于改进暗通道和导向滤波的单幅图像去雾算法［J］.自动化学报, 2016, 42(3): 455-465.
Chen S Z, Ren Z G, Lian Q S. Single Image Dehazing Algorithm Based on Improved Dark Channel Prior and Guided Filter［J］. Acta Automatica Sinica, 2016, 42(3): 455-465.
［10］杜宏博, 王丽会. 基于改进暗原色先验模型的快速图像去雾方法［J］. 计算机工程与应用, 2016, 52(1): 178-184.
Du H B, Wang L H. Fast image de-hazing method based on improved dark channel prior model［J］. Computer engineering and Applications, 2016, 52(1): 178-184.
［11］张剑飞, 杜晓听, 王波. 基于量子萤火虫和增益Beta的医学DR图像自适应增强［J］. 微电子学与计算机, 2014, 31(5): 135-139.
Zhang J F, Du X T, Wang B. Adaptive enhancement of medical DR images based on quantum firefly and gain Beta［J］. Microelectronics ＆ Computer, 2014, 31(5): 135-139.
［12］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.
［13］王泽胜, 董宝田, 赵芳璨, 等. 基于改进暗通道先验的交通图像去雾新方法［J］. 控制与决策, 2018, 33(5): 193-202.
Wang Z S, Dong B T, Zhao F C, et al. An Improved Dehazing Method for Traffic Images Based on Dark Channel Prior ［J］. Control and Decision, 2018, 33 (5): 193-202.
2019, Vol. 40 
