Abstract
Haze removal is the process by which horizontal obscuration is eliminated from hazy images captured during inclement weather. Images captured in natural environments with varied weather conditions frequently exhibit localized light sources or color-shift effects. The occurrence of these effects presents a difficult challenge for hazy image restoration, with which many traditional restoration methods cannot adequately contend. In this article, we present a new image haze removal approach based on Fisher's linear discriminant-based dual dark channel prior scheme in order to solve the problems associated with the presence of localized light sources and color shifts, and thereby achieve effective restoration. Experimental restoration results via qualitative and quantitative evaluations show that our proposed approach can provide higher haze-removal efficacy for images captured in varied weather conditions than can the other state-of-the-art approaches.
- P. N. Belhumeur, J. P. Hespanha, and D. Kriegman. 1997. Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19, 7, 711--720. DOI:http://dx.doi.org/10.1109/34.598228 Google ScholarDigital Library
- Bo-Hao Chen and Shih-Chia Huang. 2013. Improved visibility of single hazy images captured in inclement weather conditions. In Proceedings of the IEEE International Symposium on Multimedia. 267--270. DOI:http://dx.doi.org/10.1109/ISM.2013.51 Google ScholarDigital Library
- Raanan Fattal. 2008. Single image dehazing. ACM Trans. Graph. 27, 3, Article 72, DOI:http://dx.doi. org/10.1145/1360612.1360671 Google ScholarDigital Library
- Nicolas Hautire, Jean Philippe Tarel, Didier Aubert, and Ric Dumont. 2011. Blind contrast enhancement assessment by gradient ratioing at visible edges. Image Analysis & Stereology 27, 2. http://www.ias-iss.org/ojs/IAS/article/view/834Google Scholar
- Kaiming He, Jian Sun, and Xiaoou Tang. 2011. Single Image Haze Removal Using Dark Channel Prior. IEEE Trans. Pattern Anal. Mach. Intell. 33, 12, 2341--2353. DOI:http://dx.doi.org/10.1109/TPAMI.2010.168 Google ScholarDigital Library
- M. Anwar Hossain, Pradeep K. Atrey, and Abdulmotaleb El Saddik. 2011. Modeling and assessing quality of information in multisensor multimedia monitoring systems. ACM Trans. Multimedia Comput. Commun. Appl. 7, 1, Article 3, DOI:http://dx.doi.org/10.1145/1870121.1870124 Google ScholarDigital Library
- Shih-Chia Huang, Bo-Hao Chen, and Yi-Jui Cheng. 2014a. An efficient visibility enhancement algorithm for road scenes captured by intelligent transportation systems. IEEE Trans. Intell. Transp. Syst. 15, 5, 2321--2332. DOI:http://dx.doi.org/10.1109/TITS.2014.2314696Google ScholarCross Ref
- Shih-Chia Huang, Bo-Hao Chen, and Wei-Jheng Wang. 2014b. Visibility restoration of single hazy images captured in real-world weather conditions. IEEE Trans. Circuits Syst. Video Technol. 24, 10, 1814--1824. DOI:http://dx.doi.org/10.1109/TCSVT.2014.2317854Google ScholarCross Ref
- Anya Hurlbert. 1986. Formal connections between lightness algorithms. J. Opt. Soc. Amer. A 3, 10, 1684--1693. DOI:http://dx.doi.org/10.1364/JOSAA.3.001684Google ScholarCross Ref
- Wenbo Jin, Zengyuan Mi, Xiaotian Wu, Yue Huang, and Xinghao Ding. 2012. Single image de-haze based on a new dark channel estimation method. In Proceedings of the IEEE International Conference on Computer Science and Automation Engineering. Vol. 2, 791--795. DOI:http://dx.doi.org/10.1109/CSAE.2012.6272884Google ScholarCross Ref
- Johannes Kopf, Boris Neubert, Billy Chen, Michael Cohen, Daniel Cohen-Or, Oliver Deussen, Matt Uyttendaele, and Dani Lischinski. 2008. Deep photo: Model-based photograph enhancement and viewing. ACM Trans. Graph. 27, 5, Article 116, DOI:http://dx.doi.org/10.1145/1409060.1409069 Google ScholarDigital Library
- E. Y. Lam. 2005. Combining gray world and retinex theory for automatic white balance in digital photography. In Proceedings of the 9th International Symposium on Consumer Electronics. 134--139. DOI:http://dx.doi.org/10.1109/ISCE.2005.1502356Google ScholarCross Ref
- Edwin H. Land. 1986. An alternative technique for the computation of the designator in the retinex theory of color vision. Proc Natl Acad Sci USA.Google ScholarCross Ref
- A. Levin, D. Lischinski, and Y. Weiss. 2008. A closed-form solution to natural image matting. IEEE Trans. Pattern Anal. Mach. Intell. 30, 2, 228--242. DOI:http://dx.doi.org/10.1109/TPAMI.2007.1177 Google ScholarDigital Library
- Xiaotao Liu, Mark Corner, and Prashant Shenoy. 2009. SEVA: Sensor-enhanced video annotation. ACM Trans. Multimedia Comput. Commun. Appl. 5, 3, Article 24, DOI:http://dx.doi.org/10.1145/1556134.1556141 Google ScholarDigital Library
- Tao Mei, Lin-Xie Tang, Jinhui Tang, and Xian-Sheng Hua. 2013. Near-lossless semantic video summarization and its applications to video analysis. ACM Trans. Multimedia Comput. Commun. Appl. 9, 3, Article 16, DOI:http://dx.doi.org/10.1145/2487268.2487269 Google ScholarDigital Library
- S. G. Narasimhan and S. K. Nayar. 2003a. Contrast restoration of weather degraded images. IEEE Trans. Pattern Anal. Mach. Intell. 25, 6, 713--724. DOI:http://dx.doi.org/10.1109/TPAMI.2003.1201821 Google ScholarDigital Library
- Srinivasa G. Narasimhan and Shree Nayar. 2003b. Interactive deweathering of an image using physical models. In Proceedings of the IEEE Workshop on Color and Photometric Methods in Computer Vision in Conjunction with ICCV.Google Scholar
- Ko Nishino, Louis Kratz, and Stephen Lombardi. 2012. Bayesian defogging. Int. J. Comput. Vision 98, 3, 263--278. DOI:http://dx.doi.org/10.1007/s11263-011-0508-1 Google ScholarDigital Library
- J. P. Oakley and B. L. Satherley. 1998. Improving image quality in poor visibility conditions using a physical model for contrast degradation. IEEE Trans. Image Process. 7, 2, 167--179. DOI:http://dx.doi. org/10.1109/83.660994 Google ScholarDigital Library
- S. Shwartz, E. Namer, and Y. Y. Schechner. 2006. Blind haze separation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol. 2, 1984--1991. DOI:http://dx.doi.org/10.1109/CVPR.2006.71 Google ScholarDigital Library
- Lauro Snidaro, Ingrid Visentini, and Gian Luca Foresti. 2012. Fusing multiple video sensors for surveillance. ACM Trans. Multimedia Comput. Commun. Appl. 8, 1, Article 7, DOI:http://dx.doi.org/10.1145/2071396.2071403 Google ScholarDigital Library
- Shen-Chuan Tai, Tzu-Wen Liao, Yi-Ying Chang, and Chih Pei Yeh. 2012. Automatic White Balance algorithm through the average equalization and threshold. In Proceedings of the 8th International Conference on Information Science and Digital Content Technology. Vol. 3, 571--576.Google Scholar
- R. T. Tan. 2008. Visibility in bad weather from a single image. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1--8. DOI:http://dx.doi.org/10.1109/CVPR.2008.4587643Google ScholarCross Ref
- J. P Tarel and N. Hautiere. 2009. Fast visibility restoration from a single color or gray level image. In Proceedings of the IEEE 12th International Conference on Computer Vision. 2201--2208. DOI:http://dx.doi.org/10.1109/ICCV.2009.5459251Google Scholar
- Michael A. Webster. 1996. Human colour perception and its adaptation. Network: Computation in Neural Systems 7, 4, 587--634. DOI:http://dx.doi.org/10.1088/0954-898X_7_4_002Google ScholarCross Ref
- Gerhard West and Michael H. Brill. 1982. Necessary and sufficient conditions for Von Kries chromatic adaptation to give color constancy. J. Math. Biology 15, 2, 249--258. DOI:http://dx.doi.org/10.1007/BF00275077Google ScholarCross Ref
- Junwen Wu and Mohan M. Trivedi. 2010. An eye localization, tracking and blink pattern recognition system: Algorithm and evaluation. ACM Trans. Multimedia Comput. Commun. Appl. 6, 2, Article 8, 23 pages. DOI:http://dx.doi.org/10.1145/1671962.1671964 Google ScholarDigital Library
- Bin Xie, Fan Guo, and Zixing Cai. 2010. Improved single image dehazing using dark channel prior and multi-scale Retinex. In Proceedings of the International Conference on Intelligent System Design and Engineering Application, Vol. 1. 848--851. DOI:http://dx.doi.org/10.1109/ISDEA.2010.141 Google ScholarDigital Library
- Haoran Xu, Jianming Guo, Qing Liu, and Lingli Ye. 2012. Fast image dehazing using improved dark channel prior. In Proceedings of the International Conference on Information Science and Technology. 663--667. DOI:http://dx.doi.org/10.1109/ICIST.2012.6221729Google ScholarCross Ref
- Jing Yu and Qingmin Liao. 2011. Fast single image fog removal using edge-preserving smoothing. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. 1245--1248. DOI:http://dx.doi.org/10.1109/ICASSP.2011.5946636Google ScholarCross Ref
Index Terms
- An Advanced Visibility Restoration Algorithm for Single Hazy Images
Recommendations
Improved Visibility of Single Hazy Images Captured in Inclement Weather Conditions
ISM '13: Proceedings of the 2013 IEEE International Symposium on MultimediaHaze removal is the process by which horizontal obscuration is eliminated from hazy images captured during inclement weather. Sandstorms present a particularly challenging condition, images captured during sandstorms often exhibit color-shift effects ...
A Novel Visibility Restoration Algorithm for Single Hazy Images
SMC '13: Proceedings of the 2013 IEEE International Conference on Systems, Man, and CyberneticsThe visibility of outdoor images captured in inclement weather will become degraded due to the presence of haze, fog, mist, and so on. Poor visibility caused by atmospheric phenomenon in turn causes failure in computer vision applications, such as ...
Hazy Image Restoration by Bi-Histogram Modification
Regular Papers and Special Section on Intelligent Healthcare InformaticsVisibility restoration techniques are widely used for information recovery of hazy images in many computer vision applications. Estimation of haze density is an essential task of visibility restoration techniques. However, conventional visibility ...
Comments