基于显著图的可变模板形态学去雾方法

董辉; 张斌; 董辉; 张斌

doi:10.16383/j.aas.2018.c170607

[1]

Narasimhan S G, Nayar S K. Vision and the atmosphere. International Journal of Computer Vision, 2002, 48 (3): 233-254 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=b619651bb1a84a4d7a31d397fb0f9386

[2]

He K M, Sun J, Tang X O. Single image haze removal using dark channel prior. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33 (12): 2341-2353 doi: 10.1109/TPAMI.2010.168

[3]

吴迪, 朱青松.图像去雾的最新研究进展.自动化学报, 2015, 41 (2): 221-239 http://www.aas.net.cn/CN/abstract/abstract18603.shtml

Wu Di, Zhu Qing-Song. The latest research progress of image dehazing. Acta Automatica Sinica, 2015, 41 (2): 221-239 http://www.aas.net.cn/CN/abstract/abstract18603.shtml

[4]

Stark J A. Adaptive image contrast enhancement using generalizations of histogram equalization. IEEE Transactions on Image Processing, 2000, 9 (5): 889-896 doi: 10.1109/83.841534

[5]

McCann J. Lessons learned from Mondrians applied to real images and color gamuts. In: Proceedings of the IS & T/SID 7th Color and Imaging Conference. Scottsdale, USA, 1999. 1-8 https://www.researchgate.net/publication/221501975_Lessons_Learned_from_Mondrians_Applied_to_Real_Images_and_Color_Gamuts

[6]

Schechner Y Y, Narasimhan S G, Nayar S K. Instant dehazing of images using polarization. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Kauai, HI, USA: IEEE, 2001. I-325-I-332 https://www.researchgate.net/publication/3940554_Instant_dehazing_of_images_using_polarization

[7]

Kopf J, Neubert B, Chen B, Cohen M, Cohen-Or D, Deussen O, et al. Deep photo: model-based photograph enhancement and viewing. ACM Transactions on Graphics, 2008, 27 (5): Article No. 116 http://d.old.wanfangdata.com.cn/NSTLQK/NSTL_QKJJ0210187593/

[8]

Narasimhan S G, Nayar S K. Contrast restoration of weather degraded images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25 (6): 713-724 doi: 10.1109/TPAMI.2003.1201821

[9]

Narasimhan S G, Nayar S K. Chromatic framework for vision in bad weather. In: Proceedings of the 2000 IEEE Conference on Computer Vision and Pattern Recognition. Hilton Head Island, SC, USA: IEEE, 2000. 598-605 https://www.researchgate.net/publication/3854198_Chromatic_framework_for_vision_in_bad_weather

[10]

Nayar S K, Narasimhan S G. Vision in bad weather. In: Proceedings of the 7th IEEE International Conference on Computer Vision. Kerkyra, Greece: IEEE, 1999. 820-827

[11]

Zhu Q S, Mai J M, Shao L. A fast single image haze removal algorithm using color attenuation prior. IEEE Transactions on Image Processing, 2015, 24 (11): 3522-3533 doi: 10.1109/TIP.2015.2446191

[12]

Li Z G, Zheng J H. Edge-preserving decomposition-based single image haze removal. IEEE Transactions on Image Processing, 2015, 24 (12): 5432-5441 doi: 10.1109/TIP.2015.2482903

[13]

Caraffa L, Tarel J P. Markov random field model for single image defogging. In: Proceedings of the 2013 IEEE Intelligent Vehicles Symposium (Ⅳ). Gold Coast, QLD, Australia: IEEE, 2013. 994-999 https://www.researchgate.net/publication/261225195_Markov_Random_Field_Model_for_Single_Image_Defogging

[14]

刘海波, 杨杰, 吴正平, 张庆年, 邓勇.基于暗通道先验和Retinex理论的快速单幅图像去雾方法.自动化学报, 2015, 41 (7): 1264-1273 http://www.aas.net.cn/CN/abstract/abstract18700.shtml

Liu Hai-Bo, Yang Jie, Wu Zheng-Ping, Zhang Qing-Nian, Deng Yong. A fast single image dehazing method based on dark channel prior and Retinex theory. Acta Automatica Sinica, 2015, 41 (7): 1264-1273 http://www.aas.net.cn/CN/abstract/abstract18700.shtml

[15]

Chen J, Chau L P. Heavy haze removal in a learning framework. In: Proceedings of the 2015 IEEE International Symposium on Circuits and Systems. Lisbon, Portugal: IEEE, 2015. 1590-1593

[16]

Tang K T, Yang J C, Wang J. Investigating haze-relevant features in a learning framework for image dehazing. In: Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition. Columbus, OH, USA: IEEE, 2014. 2995-3002 https://www.researchgate.net/publication/286594615_Investigating_Haze-Relevant_Features_in_a_Learning_Framework_for_Image_Dehazing

[17]

Choi L, You J, Bovik A C. Referenceless prediction of perceptual fog density and perceptual image defogging. IEEE Transactions on Image Processing, 2015, 24 (11): 3888-3901 doi: 10.1109/TIP.2015.2456502

[18]

Cai B L, Xu X M, Jia K, Qing C M, Tao D C. DehazeNet: an end-to-end system for single image haze removal. IEEE Transactions on Image Processing, 2016, 25 (11): 5187-5198 doi: 10.1109/TIP.2016.2598681

[19]

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.自动化学报, 2016, 42 (3): 455-465 http://www.aas.net.cn/CN/abstract/abstract18833.shtml

Chen Shu-Zhen, Ren Zhan-Guang, Lian Qiu-Sheng. Single image dehazing algorithm based on improved dark channel prior and guided filter. Acta Automatica Sinica, 2016, 42 (3): 455-465 http://www.aas.net.cn/CN/abstract/abstract18833.shtml

[20]

He K M, Sun J, Tang X O. Guided image filtering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35 (6): 1397-1409 doi: 10.1109/TPAMI.2012.213

[21]

Tarel J P, Hautiere N. Fast visibility restoration from a single color or gray level image. In: Proceedings of the 2009 IEEE 12th International Conference on Computer Vision. Kyoto, Japan: IEEE, 2009. 2201-2208 https://www.researchgate.net/publication/221110862_Fast_Visibility_Restoration_from_a_Single_Color_or_Gray_Level_Image

[22]

Kim J H, Jang W D, Sim J Y, Kim C S. Optimized contrast enhancement for real-time image and video dehazing. Journal of Visual Communication and Image Representation, 2013, 24 (3): 410-425 doi: 10.1016/j.jvcir.2013.02.004

[23]

Meng G F, Wang Y, Duan J Y, Xiang S M, Pan C H. Efficient image dehazing with boundary constraint and contextual regularization. In: Proceedings of the 2013 IEEE International Conference on Computer Vision. Sydney, NSW, Australia: IEEE, 2013. 617-624 https://www.researchgate.net/publication/262356211_Efficient_Image_Dehazing_with_Boundary_Constraint_and_Contextual_Regularization

[24]

Levin A, Lischinski D, Weiss Y. A closed-form solution to natural image matting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30 (2): 228-242 doi: 10.1109/TPAMI.2007.1177

[25]

Xiao C X, Liu M, Xiao D L, Dong Z, Ma K L. Fast closed-form matting using a hierarchical data structure. IEEE Transactions on Circuits and Systems for Video Technology, 2014, 24 (1): 49-62 doi: 10.1109/TCSVT.2013.2276153

[26]

Huang S C, Chen B H, Cheng Y J. An efficient visibility enhancement algorithm for road scenes captured by intelligent transportation systems. IEEE Transactions on Intelligent Transportation Systems, 2014, 15 (5): 2321-2332 doi: 10.1109/TITS.2014.2314696

[27]

Li X Y, Gu Y, Hu S M, Martin R R. Mixed-domain edge-aware image manipulation. IEEE Transactions on Image Processing, 2013, 22 (5): 1915-1925 doi: 10.1109/TIP.2013.2237922

[28]

Huang S C, Chen B H, Wang W J. Visibility restoration of single hazy images captured in real-world weather conditions. IEEE Transactions on Circuits and Systems for Video Technology, 2014, 24 (10): 1814-1824 doi: 10.1109/TCSVT.2014.2317854

[29]

Lai Y H, Chen Y L, Chiou C J, Hsu C T. Single-image dehazing via optimal transmission map under scene priors. IEEE Transactions on Circuits and Systems for Video Technology, 2015, 25 (1): 1-14 doi: 10.1109/TCSVT.2014.2329381

[30]

Li Z G, Zheng J H, Zhu Z J, Yao W, Wu S Q. Weighted guided image filtering. IEEE Transactions on Image Processing, 2015, 24 (1): 120-129 doi: 10.1109/TIP.2014.2371234

[31]

Curic V, Hendriks C L, BorgeforsG. Salience adaptive structuring elements. IEEE Journal of Selected Topics in Signal Processing, 2012, 6 (7): 809-819 doi: 10.1109/JSTSP.2012.2207371

[32]

Wang Z, Bovik A C, Sheikh H R, Simoncelli E P. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 2004, 13 (4): 600-612 doi: 10.1109/TIP.2003.819861