Fast Visibility Restoration of Single Image by Progressive Scene Transmission Estimation

LIAO Bin; YIN Peng; ZHAO Jianhui

doi:10.11999/JEIT150515

Volume 38 Issue 1

Jan. 2016

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LIAO Bin, YIN Peng, ZHAO Jianhui. Fast Visibility Restoration of Single Image by Progressive Scene Transmission Estimation[J]. Journal of Electronics & Information Technology, 2016, 38(1): 15-22. doi: 10.11999/JEIT150515

Citation:

LIAO Bin, YIN Peng, ZHAO Jianhui. Fast Visibility Restoration of Single Image by Progressive Scene Transmission Estimation[J]. Journal of Electronics & Information Technology, 2016, 38(1): 15-22. doi: 10.11999/JEIT150515

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Fast Visibility Restoration of Single Image by Progressive Scene Transmission Estimation

doi: 10.11999/JEIT150515

1.
(School of Computer Science and Information Engineering, Hubei University, Wuhan 430062, China)
2.
(School of Computer Science and Information Engineering, Hubei University, Wuhan 430062, China)

Funds:

The National Natural Science Foundation of China (61300125)

Received Date: 2015-05-04
Rev Recd Date: 2015-08-28
Publish Date: 2016-01-19

Abstract

Abstract

A fast visibility restoration method of single image by progressive scene transmission estimation is proposed. Based on the boundary conditions of scene radiance and the atmosphere scattering model, the initial value of the scene transmission is estimated and refined with recursive bilateral filtering. The restoration result is decomposed into a base layer and a detail layer by gradient domain recursive bilateral filtering. The high visibility?restoration result is obtained with tone mapping of the base layer and detail enhancement. Utilizing Gaussian KD tree, the high dimensional feature space of the original image is subdivided adaptively to obtain the Gaussian sampling and accelerate the restoration computing. Compared with related work, the proposed method preserves edges and details, avoiding the halo effectively. The objective indicators are applied to evaluate the restoration results. The experiment results show that the proposed method is effective and feasible, and the restoration results accord with the real scene better.
- Image processing,
- Visibility restoration,
- Recursive bilateral filtering,
- Adaptive sampling

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References(24)

References

TAREL J P, HAUTIERE N, CORD A, et al.. Improved visibility of road scene images under heterogeneous fog[C]. 2010 IEEE Intelligent Vehicles Symposium (IV), San Diego, 2010: 478-485.

南栋, 毕笃彦, 查宇飞, 等. 基于参数估计的无参考型图像质量评价算法[J]. 电子与信息学报, 2013, 35(9): 2066-2072. doi: 10.3724/SP.J.1146.2012.01652.

NAN Dong, BI Duyan, ZHA Yufei, et al. A no-reference image quality assessment method based on parameter estimation[J]. Journal of Electronics Information Technology, 2013, 35(9): 2066-2072. doi: 10.3724/SP.J.1146. 2012.01652.

吴炜, 李勃, 杨娴, 等. 基于路面视亮度差平方最优化的视频能见度检测算法[J]. 电子与信息学报, 2014, 36(10): 2412-2418. doi: 10.3724/SP.J.1146.2013.01743.

WU Wei, LI Bo, YANG Xian, et al. Visibility detection algorithm based on optimization of squared differences upon apparent luminance of roads[J]. Journal of Electronics Information Technology, 2014, 36(10): 2412-2418. doi: 10.3724/SP.J.1146.2013.01743.

HE K, SUN J, and TANG X. Guided image filtering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6): 1397-1409.

褚宏莉, 李元祥, 周则明, 等. 基于黑色通道的图像快速去雾优化算法[J]. 电子学报, 2013, 41(4): 791-797.

CHU Hongli, LI Yuanxiang, ZHOU Zeming, et al. Optimized fast dehazing method based on dark channel prior[J]. Acta Electronica Sinica, 2013, 41(4): 791-797.

薛模根, 周浦城, 张洪坤. 利用方向延伸专家场的单幅雾天图像复原[J]. 计算机辅助设计与图形学学报, 2014, 26(5): 782-787.

XUE mogen, ZHOU Pucheng, and ZHANG Hongkun. Single foggy image restoration using orientation extended fields of experts[J]. Journal of Computer Aided Design Graphics, 2014, 26(5): 782-787.

郭璠, 唐琎, 蔡自兴. 基于融合策略的单幅图像去雾算法[J]. 通信学报, 2014, 35(7): 199-207.

GUO Fan, TANG Jin, and CAI Zixing. Single image defogging based on fusion strategy[J]. Journal on Communications, 2014, 35(7): 199-207.

吴迪, 朱青松. 图像去雾的最新研究进展[J]. 自动化学报, 2015, 41(2): 221-239.

WU Di and ZHU Qingsong. The latest research progress of

image dehazing[J]. Acta Automatica Sinica, 2015, 41(2): 221-239.

McCann J J. Retinex at 40[J]. Journal of Electronic Imaging, 2004, 13(1): 6-7.

FATTAL R. Single image dehazing[J]. ACM Transactions on Graphics, 2008, 27(3): 1-9.

HE K, SUN J, and TANG X. Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12): 2341-2353.

TAREL J P and HAUTIERE N. Fast visibility restoration from a single color or gray level image[C]. 2009 IEEE 12th International Conference on Computer Vision, Kyoto, 2009: 2201-2208.

TAN R T. Visibility in bad weather from a single image[C]. IEEE Conference on Computer Vision and Pattern Recognition(CVPR), Alaska, 2008: 1-8.

YANG Q. Recursive bilateral filtering[C]. European Conference on Computer VisionECCV, Springer Berlin Heidelberg, 2012: 399-413.

DRAGO F, MYSZKOWSKI K, ANNEN T, et al.. Adaptive logarithmic mapping for displaying high contrast scenes[J]. Computer Graphics Forum, 2003, 22(3): 419-426.

郭璠, 蔡自兴. 图像去雾算法清晰化效果客观评价方法[J]. 自动化学报, 2012, 38(9): 1410-1419.

GUO Fan and CAI Zixing. Objective assessment method for the clearness effect of image defogging algorithm[J]. Acta Automatica Sinica, 2012, 38(9): 1410-1419.

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