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http://dx.doi.org/10.5762/KAIS.2019.20.12.1

Low Complexity Single Image Dehazing via Edge-Preserving Transmission Estimation and Pixel-Based JBDC  

Kim, Jongho (Department of Multimedia Engineering, Sunchon National University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.20, no.12, 2019 , pp. 1-7 More about this Journal
Abstract
This paper presents low-complexity single-image dehazing to enhance the visibility of outdoor images that are susceptible to degradation due to weather and environmental conditions, and applies it to various devices. The conventional methods involve refinement of coarse transmission with high computational complexity and extensive memory requirements. But the proposed transmission estimation method includes excellent edge-preserving performance from comparison of the pixel-based dark channel and the patch-based dark channel in the vicinity of edges, and transmission can be estimated with low complexity since no refinement is required. Moreover, it is possible to accurately estimate transmissions and adaptively remove haze according to the characteristics of the images via prediction of the atmospheric light for each pixel using joint bright and dark channel (JBDC). Comprehensive experiments on various hazy images show that the proposed method exhibits reduced computational complexity and excellent dehazing performance, compared to the existing methods; thus, it can be applied to various fields including real-time devices.
Keywords
Dehazing; JBDC; Refinement; Single Image Dehazing; Transmission Estimation;
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Times Cited By KSCI : 4  (Citation Analysis)
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1 Y. Schechner, S. Narasimhan, and S. Nayer, "Instant dehazing of images using polarization," Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR ), IEEE, Kauai, USA, pp. 325-332, Dec. 2001. DOI: http://dx.doi.org/10.1109/CVPR.2001.990493
2 S. Shwartz, E. Namer, and Y. Schechner, "Blind haze separation," Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR ), IEEE, New York, USA, pp. 1984-1991, Jun. 2006. DOI: http://dx.doi.org/10.1109/CVPR.2006.71
3 S. Narasimhan and S. Nayer, "Contrast restoration of weather degraded images," IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 25, No. 6, pp. 713-724, Jun. 2003. DOI: http://dx.doi.org/10.1109/TPAMI.2003.1201821   DOI
4 S. Nayer and S. Narasimhan, "Vision in bad weather," Proceedings of IEEE Int. Conference on Computer Vision (ICCV ), IEEE, Kerkyra, Greece, pp. 820-827, Sep. 1999. DOI: http://dx.doi.org/10.1109/ICCV.1999.790306
5 J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, "Deep photo: Model-based photograph enhancement and viewing," ACM Trans. Graphics, Vol. 27, No. 5, pp. 116:1-116:10, Dec. 2008. DOI: http://dx.doi.org/10.1145/1409060.1409069
6 S. Lee, S. Yun, J. Nam, C. Won, and S. Jung, "A review on dark channel prior based image dehazing algorithms," The European Association for Signal Processing (EURASIP) Journal on Image and Video Processing, Vol. 2016, No. 4, pp. 1-23, Dec. 2016. DOI: http://dx.doi.org/10.1186/s13640-016-0104-y
7 R. Tan, "Visibility in bad weather from a single image," Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, Anchorage, USA, pp. 1-8, Jun. 2008. DOI: http://dx.doi.org/10.1109/CVPR.2008.4587643
8 R. Fattal, "Single image dehazing," ACM Trans. Graphics, Vol. 27, No. 3, pp. 1-9, Aug. 2008. DOI: http://dx.doi.org/10.1145/1360612.1360671   DOI
9 J. Kim, "Histogram modification based on additive term and gamma correction for image contrast enhancement," Journal of the Korea Institute of Electronic Communication Sciences, Vol. 13, No. 5, pp. 1117-1124, Oct. 2018.   DOI
10 K. He, J. Sun, and X. Tang, "Single image haze removal using dark channel prior," IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 33, No. 12, pp. 2341-2353, Dec. 2011. DOI: http://dx.doi.org/10.1109/TPAMI.2010.168   DOI
11 J. Kim, "Single image haze removal algorithm using dual DCP and adaptive brightness correction," Journal of the Korea Academia-Industrial cooperation Society, Vol. 19, No. 11, pp. 31-37, Nov. 2018. DOI: http://dx.doi.org/10.5762/KAIS.2018.19.11.31
12 W. Oh and J. Kim, "Single image haze removal technique via pixel-based joint BDCP and hierarchical bilateral filter," Journal of the Korea Institute of Electronic Communication Sciences, Vol. 14, No. 1, pp. 257-264, Feb. 2019.   DOI
13 J. Kim, "Efficient single image dehazing by pixel-based JBDCP and low complexity transmission estimation," Journal of the Korea Institute of Electronic Communication Sciences, Vol. 14, No. 5, pp. 977-984, Oct. 2019.
14 S. Salazar-Colores, J. Ramos-Arreguin, J. Pedraza-Ortega, and J. Rodriguez-Resendiz, "Efficient single image dehazing by modifying the dark channel prior," The European Association for Signal Processing (EURASIP ) Journal on Image and Video Processing, Vol. 2019:66, No. 1, pp. 1-8, May 2019. DOI: http://dx.doi.org/10.1186/s13640-019-0447-2
15 J. Tarel and N. Hautiere, "Fast visibility restoration from a single color or gray level images," Proceedings of IEEE Int. Conference on Computer Vision (ICCV ), IEEE, Kyoto, Japan, pp. 2201-2208, Sep. 2009. DOI: http://dx.doi.org/10.1109/ICCV.2009.5459251
16 Z. Mi, H. Zhou, Y. Zheng, and M. Wang, "Single image dehazing via multi-scale gradient domain contrast enhancement," IET Image Processing, Vol. 10, No. 3, pp. 206-214, Mar. 2016. DOI: http://dx.doi.org/10.1049/iet-ipr.2015.0112   DOI
17 A. Levin D. Lischinski, and Y. Weiss, "A closed form solution to natural image matting," IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 30, No. 2, pp. 228-242, Feb. 2008. DOI: http://dx.doi.org/10.1109/TPAMI.2007.1177   DOI
18 C. Yeh, L. Kang, M. Lee, and C. Lin, "Haze effect removal from image via haze density estimation in optical model," Optics Express, Vol. 21, No. 22, pp. 27127-27141, Nov. 2013. DOI: http://dx.doi.org/10.1364/OE.21.027127   DOI