結合白區塊視網膜皮層理論與改良暗通道先驗之單張影像除霧

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姓名

陳郁姍(Yu-Shan,Chen) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

結合白區塊視網膜皮層理論與改良暗通道先驗之單張影像除霧
(Single Image Haze Removal Using White-Patch Retinex Theory and Modified Dark Channel Prior)

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至系統瀏覽論文 ( 永不開放)

摘要(中)

在本文中我們提出一個能夠有效復原有霧影像的方法。透過白區塊視網膜皮層理論和改良的暗通道先驗演算法，除了獲得清晰影像，也能夠解決暗通道先驗所產生的1)光暈效應2)色彩失真3)運算時間過長的問題。並於文末比較此兩演算法的優缺點及有效性以證實本文所提出的方法的可應用性。

摘要(英)

In this paper, we propose a simple but effective method to remove haze from a single input image using white-patch retinex and modified dark channel prior. In this way, we can not only restore the hazy images but also overcome three problems caused by dark channel prior, which are the halo effect along depth discontinuities in recovered images, the color distortion is serious in some weather conditions and the time-consuming process. Finally, we compare our proposed method with the dark channel prior and analyze their pros and cons.

關鍵字(中)

★ 暗通道先驗
★ 白區塊視網膜皮層理論
★ 引導影像濾波器
★ 影像除霧

關鍵字(英)

★ dark channel prior
★ white-patch retinex
★ guide filter
★ haze removal

論文目次

目錄
中文摘要 vi
Abstract vii
目錄 ix
圖目錄 xii
表目錄 xv
第一章緒論 1
1.1研究背景 1
1.2文獻回顧 2
1.2.1影像除霧物理模型 2
1.2.2直方圖均化 3
1.2.3 多張影像除霧 3
1.2.4 單張影像除霧 4
1.3研究動機與方法 5
1.4.研究成果與貢獻 5
1.5論文架構 7
第二章研究方法 8
2.1基於暗通道先驗的影像去霧 8
2.1.1暗通道先驗 8
2.1.2透射率估測 9
2.1.3軟擷取圖像 11
2.1.4大氣光估測 12
2.1.5 復原清晰影像 13
2.2 討論 14
2.2.1色彩失真 14
2.2.2 光暈效應 16
2.2.3運算速度 17
2.3白區塊視網膜皮層理論 17
2.3.1色彩恆常性 17
2.3.2白區塊視網膜皮層理論 18
2.4強化透射率 23
2.4.1最小值濾波器中值濾波器與介紹與比較 24
2.5 引導影像濾波器 28
2.6 大氣光估測 30
2.7 影像復原 30
2.8 實驗流程 31
第三章實驗結果與討論 33
3.1除霧結果比較 33
3.1.1光暈效應 33
3.1.2色彩失真 36
3.1.3運算速度 40
3.2影像品質檢測 43
第四章結論與建議 47
4.1 結論 47
4.2 建議 48
參考文獻 49

參考文獻

[1]S. K. Nayar, and S. G. Narashiman, “Vision in bad weather”, ICCV, Vol. 2, pp. 820 – 827, Sep, 1999.
[2] E. J. McCartney, Optics of the atmosphere: scattering by molecules and particles, New York, John Wiley and Sons, Inc. 1976.
[3] H. Koschmieder. Theorie der horizontalen sichtweite. Beitr. Phys. freien Atm., 1924.
[4] W. Wang, X. Yuan, X. Wu, Y. Liu, “Fast Image Dehazing Method Based on Linear Transformation”, IEEE Transactions on Multimedia, Vol.19, no. 6, pp. 1142 – 1155, Jun, 2017.
[5] T. K. Kim, J. K. Paik and B. S. Kang. “Contrast enhancement system using spatially adaptive histogram equalization with temporal filtering”, IEEE Trans. TCE., Vol. 44, no. 1, pp. 82-87, Feb, 1998.
[6] SJ. A. Stark. “Adaptive image contrast enhancement using generalizations of histogram equalization”, IEEE Trans. TIP., Vol. 9, no. 5, pp. 889-896, May, 2000.
[7] S. G. Narasimhan and S. K. Nayar, “Chromatic framework for vision in bad weather”, CVPR, Vol.1, pp. 598 – 605, 2000.
[8] S. G. Narasimhan, and S. K. Nayar, “Contrast restoration of weather degraded images”, IEEE Trans. on PAMI., Vol. 25, no. 6, pp. 713-724, 2003.
[9] S. G. Narasimhan, and S. K. Nayar. “Interactive deweathering of an image using physical model”, IEEE Workshop on color and photometric Methods in computer Vision, Vol. 6, pp. 1-8, 2003.
[10] J. Kopt, B. Neubert, B. Chen, M. Cohen and D. Cohen-Or. “Deep photo: Model-based photograph enhancement and viewing”, ACM Transactions on Graphics, Vol. 27, no. 5, pp. 116:1-116:10, Dec, 2008.
[11] N. Hautiere, J. Tarel, and D. Aubert, “Towards fog-free in-vehicle vision systems through contrast restoration”, Proc. IEEE Conf. Computer Vision, Pattern Recognition, pp.1-8, June, 2007.
[12] S. Shwartz, E. namer, and Y. Schechner, “Blind haze separation”, Proc. IEEE Int. Conf. Computer Vision, Pattern Recognition, Vol. 2, pp.1984-1991, Oct, 2006.
[13] Y. Y. Schechner, S. G. Narasimhan, and S. K. Nayar. “Instant dehazing of images using polarization”, CVPR, Vol.1, pp. I-325 - I-332, Dec, 2001.
[14] J. Mai, Q. Zhu, D. Wu, Y. Xie, and L. Wang, “Back propagation neural network dehazing”, Proc. IEEE Conf. Robotics and Biomimetics, pp. 1433–1438, Dec, 2014.
[15]R. Fattal, “Single image dehazing”, ACM Trans. Graphics, Vol.27, no. 3, pp. 721-729, 2008.
[16] R. Tan, “Visibility in Bad Weather from a Single Image”, Proc.IEEE Conf. Computer Vision and Pattern Recognition, pp.1-8, June, 2008.
[17]K. M. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior”, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 33, no. 12, pp. 2341–2353, Dec, 2011.
[18]X. Ji, J. Cheng, J. Bai, T. Zhang, and M. Wang, “Real-time Enhancement of Image Clarity for Traffic Video Monitoring System in Haze”, Image and Signal Processing(CISP), 2014 7th International Congress, pp.11–15, Oct, 2014.
[19] Y. H. Shiau, H. Y. Yang, P. Y. Chen, and Y. Z. Chuang, “Hardware implementation of a fast and efficient haze removal method”, IEEE Trans. Circuits Syst. Video Technol., Vol. 23, no. 8, pp. 1369–1374, Aug, 2013.
[20] B. Zhang ,J. Zhao, “Hardware Implementation for Real-Time Haze Removal”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol. 25, no.3, pp. 1188-1192, Mar, 2017.
[21] M. M. El-Hashash, H. A. Aly, T. A. Mahmoud, “A video haze removal system on heterogeneous cores”, Signal and Information Processing (GlobalSIP), pp. 1255-1259, Dec, 2015.
[22] D. Nair, P. Sankaran, “A modified dark channel prior for improved dehazing”, IEEE Intelligent Computational Systems (RAICS), pp. 55-59, Dec, 2015
[23] 京華時報，北京受4年来最严重大风沙尘袭击 5级重污染(图)， 2010年 03月21日，取自http://news.sohu.com/20100321/n270974479.shtml.
[24] 成都晚報，台灣出現有史以來最嚴重沙塵汙染，2010年03月21日，取自 http://dailynews.sina.com/bg/chn/chnpolitics/sinacn/20100321/15461279725.html
[25] 蘋果日報，強烈沙塵今襲台，取自http://www.appledaily .com.tw/appledaily/article/supplement/20100321/32377006/
[26] G. Meng, Y. Wang, J. Duan, S. Xiang, and C. Pan, “Efficient image dehazing with boundary constraint and contextual regularization,” in Proc. ICCV, pp. 617– 624, Dec, 2013.
[27] Q. Zhu, J. Mai, L. Shao, “A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior”, IEEE Transactions on Image Processing, Vol. 24, no. 11, pp. 3522-3533, June, 2015.
[28] X. Lu, G. Lv, T. Lei, “Fast single image dehazing algorithm”, Audio, Language and Image Processing (ICALIP), pp. 341-346, Jul, 2014.
[29] Y. Cho, Y.-S. Shin, A. Kim, “Online depth estimation and application to underwater image dehazing”, OCEANS 2016 MTS/IEEE Monterey, pp.1-7, Sep. 2016.
[30] C.-H. Hsieh, Y.-S. Lin, C.-H. Chang, “Haze removal without transmission map refinement based on dual dark channels”, International Conference on Machine Learning and Cybernetics, Vol. 2, pp. 512-516, Jul, 2014.
[31] J. Long, Z. Shi, and W. Tang, “Fast haze removal for a single remote sensing image using dark channel prior”, in Computer Vision in Remote Sensing (CVRS), 2012 International Conference on, pp. 132 –135, Dec. 2012.
[32] C-H Hsieh, C-Y Chen, Y-J Dai, “Single image dehazing based on pixel minimum channel”, Computational Intelligence (SSCI), pp.1-5, Dec, 2016.
[33] C. Hu, G. Zhai , D. Li, “An Augmented-Reality night vision enhancement application for see-through glasses”, Multimedia & Expo Workshops (ICMEW), pp.1-6, Jul, 2015.
[34] X. Pan, F. Xie, Z. Jiang, and J. Yin, “Haze removal for a single remote sensing image based on deformed haze imaging model”, IEEE Signal Process. Lett., Vol. 22, no. 10, pp. 1806–1810, Oct, 2015.
[35] Y. Wang and C. Fan, “Single image defogging by multiscale depth fusion”, IEEE Trans. Image Process., Vol. 23, no. 11, pp. 4826–4837, Nov. 2014.
[36] A. Levin, D. Lischinski, and Y. Weiss, “A Closed Form Solution to Natural Image Matting”, Proc. IEEE Conf. Computer Vision and Pattern Recognition, Vol.1, no. 2, pp. 61- 68, Dec. 2007.
[37] S.-C. Huang, B.-H. Chen, and W.-J. Wang, “Visibility restoration of single hazy images captured in real-world weather conditions”, IEEE Trans. Circuits Syst. Video Technol., Vol. 24, no. 10, pp.1814-1824, Oct, 2014.
[38] M. Fairchild, Color Appearance Models, H. Wiley, Ed. Wiley, Hoboken, 2005.
[39] V. Agarwal, B. R. Abidi, A. Koschan, and M. A. Abidi, “An overview of color constancy algorithms”, Journal of Pattern Recognition Research, Vol. 1, pp. 42–54, 2006.
[40] S. Zeki, A vision of the brain, J. Wiley and sons, Eds. Wiley-Blackwell, January 15, 1993.
[41] Sun K, Wang B, Zhou Z Q, et al. “Combining Color Constancy and Gamma Correction for Image Enhance”, Electronics, Robotics and Automotive Mechanics Conference (CERMA), 2012 IEEE Ninth, pp. 25-30, Nov, 2012.
[42] E. H. Land, “The Retinex theory of colour vision”, Proceedings, Royal Institution of Great Britain, London, Britain, pp. 23–58, 1974.
[43] E. H. Land and J. J. McCann, “Lightness and retinex theory”, J. Opt. Soc. Am., Vol. 61, no. 1, pp. 1–11, 1971.
[44] G. D. Finlayson, S. D. Hordley, C. Lu, and M. S. Drew, “On the removal shadows from images”, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 28, no. 1, pp. 59–68, 2006.
[45] M. Ebner, Color Constancy, 1st ed., J. Wiley and Sons, Eds. Wrzburg, Germany: Wiley Publishing, 2007.
[46] K. Gibson, D. Vo, T. Nguyen, “An Investigation in dehazing compressed images and Vvdeo”, Proceedings of IEEE OCEANS Conference (OCEANS’ 10), pp.1-8, Sep, 2010.
[47] S. K, W. B, Z. Z Q, et al. “Real Time Image Haze Removal Using Bilateral Filter”, Transactions of Beijing Institute of Technology, pp. 810-811, Jul, 2011.
[48] S. Furukawa, T. Fukuda, T. Koga, N. Suetakeand, E. Uchino, ” High-Speed Min-Max Bilateral FilterBased Image Dehazing by Using GPGPU”, Advanced Mechatronic Systems, Kumamoto, Japan, pp: 459- 462, Aug, 2014.
[49] K. Sun, B. Wang, Z. Zheng and Z. Zhou, “Fast Single Image Dehazing Using Iterative Bilateral Filter”, Information Engineering and Computer Science (ICIECS), pp.1-4, Dec, 2010.
[50] K. He, J. Sun, and X. Tang, “Guided image filtering”, The European Conference on Computer Vision (ECCV), Vol. 35, no.6, pp. 1397 – 1409, Oct, 2012.
[51] D. M. Chandler, K. H. Lim, and S. S. Hemami, “Effects of spatial correlations and global precedence on the visual fidelity of distorted images”, Electronic Imaging 2006, International Society for Optics and Photonics, pp. 60 570F–60 570F, Feb, 2006.
[52]N. Hautiere, J.-P. Tarel, D. Aubert, E. Dumont et al., “Blind contrast enhancement assessment by gradient ratioing at visible edges”, Image Analysis & Stereology Journal, Vol. 27, no. 2, pp. 87–95, 2008.
[53] Y. Lee, K. Hirakawa, T. Q. Nguyen, “Joint Defogging and Demosaicking”, IEEE Transactions on Image Processing, Vol.26, no. 6, pp.3051-3063, Jun, 2017.
[54] C.O Ancuti and C. Ancuti, “Single image dehazing by multi-scale fusion”, IEEE Trans. Image Processing, Vol.22, no.8, pp. 3271- 3282, Aug, 2013.
[55] Qingsong Zhu, Jiaming Mai, Zhan Song, Di Wu, Jianjun Wang, Lei Wang, “Mean shift-based single image dehazing with re-refined transmission map”, 2014 IEEE International Conference, Systems, Man and Cybernetics (SMC), pp.4058-4064, Oct, 2014.

指導教授

鍾鴻源(Hung-Yuan Chung)

審核日期

2018-1-10

推文