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Transmission estimation is the most challenging part for single image haze removal and very sensitive to environment noise. However, most existing single image dehazing algorithms are far from satisfactory in terms of restoring an image’s details and noise removal. To address this issue, an improved haze imaging model with transmission refinement based on dark channel prior is constructed to preserve the edge details and enhance visibility. Then, a fast single image dehazing algorithm called TSGA algorithm is proposed for complex real-world images. A refined transmission map obtained by TGVSH regularity scheme provides more edges and finer details and is less susceptible to noise. Guided filter and adaptive histogram equalization greatly enhance the visibility and color contrast of the scenes and significantly improve the drawback of halo artifacts. A large quantity of comparative experiment results demonstrate that the proposed algorithm simultaneously removes the serious effect of haze and noise, effectively makes the restored images look more natural, and has a lower time complexity. All these make it a good candidate for image segmentation, object recognition, and target tracking in complex real-world weather conditions.
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Fattal R. Single image dehazing. ACM transactions on graphics (TOG). ACM. 2008;27(3):72.
Tan RT. Visibility in bad weather from a single image. 2008 I.E. Conference on Computer Vision and Pattern Recognition. CVPR 2008. IEEE, 2008. p. 1–8.
Kopf J, Neubert B, Chen B, Cohen M, Cohen-Or D, Deussen O, Lischinski D. Deep photo: model-based photograph enhancement and viewing. ACM transactions on graphics (TOG). ACM. 2008;27(5):116.
Tarel JP, Hautiere N. Fast visibility restoration from a single color or gray level image. 2009 I.E. 12th International Conference on Computer Vision. IEEE, 2009. p. 2201–2208.
Nishino K, Kratz L, Lombardi S. Bayesian defogging. Int J Comput Vis. 2012;98(3):263–78. CrossRef
Fattal R. Dehazing using color-lines. ACM transactions on graphics (TOG). 2014;34(1):13. CrossRef
Li J, Zhang H, Yuan D, Wang H. Haze removal from single images based on a luminance reference model. 2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR). IEEE, 2013. p. 446–450.
Wang Z, Feng Y. Fast single haze image enhancement. Computers & electrical engineering. 2014;40(3):785–95. CrossRef
Qin B, Huang Z, Zeng F, Ji Y. Fast single image dehazing with domain transformation-based edge- preserving filter and weighted quadtree subdivision. 2015 I.E. International Conference on Image Processing (ICIP). IEEE, 2015. p. 4233–4237.
Huang SC, Ye JH, Chen BH. An advanced single-image visibility restoration algorithm for real-world hazy scenes. IEEE Trans Ind Electron. 2015;62(5):2962–72. CrossRef
Li Y, Miao Q, Song J, Quan Y, Li W. Single image haze removal based on haze physical characteristics and adaptive sky region detection. Neurocomputing. 2016;182:221–34. CrossRef
Sun W, Wang H, Sun C, Guo B, Jia W, Sun M. Fast single image haze removal via local atmospheric light veil estimation. Computers & electrical engineering. 2015;46:371–83. CrossRef
Hui L, Peng H. An improved sharpening algorithm for foggy picture based on dark-channel prior. International Industrial Informatics and Computer Engineering Conference (IIICEC). 2015. p. 2099–2104.
Cao L, Shao X, Liu F, Wang L. Dehazing method through polarimetric imaging and multi-scale analysis. SPIE sensing technology applications. International Society for Optics and Photonics. 2015. p. 950111–8.
Shi Z, Long J, Tang W, Zhang C. Single image dehazing in inhomogeneous atmosphere. Optik - international journal for light and electron optics. 2014;125(15):3868–75. CrossRef
Tripathi AK, Mukhopadhyay S. Single image fog removal using anisotropic diffusion. IET Image Process. 2012;6(7):966–75. CrossRef
Ansia S, Aswathy AL. Single image haze removal using white balancing and saliency map. Procedia computer science. 2015;46:12–9. CrossRef
Song Y, Luo H, Hui B, Chang Z. An improved image dehazing and enhancing method using dark channel prior. Control and Decision Conference (CCDC), 2015 27th Chinese. IEEE, 2015. p. 5840–5845.
Ancuti CO, Ancuti C, Hermans C, Bekaert P. A fast semi-inverse approach to detect and remove the haze from a single image. Asian Conference on Computer Vision. Springer berlin heidelberg; 2010. p. 501–514.
Gibson KB, Nguyen TQ. Fast single image fog removal using the adaptive wiener filter. 2013 20th IEEE International Conference on Image Processing (ICIP). IEEE, 2013. p. 714–718.
Saggu MK, Singh S. A review on various haze removal techniques for image processing. International journal of current engineering and technology. 2015;5(3):1500–5.
Kaftory R, Schechner YY, Zeevi YY. Variational distance-dependent image restoration. IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2007. p. 1–8.
Joshi N, Cohen MF. Seeing Mt. Rainier: Lucky imaging for multi-image denoising, sharpening, and haze removal. 2010 I.E. International Conference on Computational Photography (ICCP). IEEE, 2010. p. 1–8.
Fang S, Wang F, Zhan J, Cao Y, Yuan H, Rao R. Simultaneous dehazing and denoising of single hazing image. Pattern recognition and artificial intelligence. 2012;25(1):136–42.
Matlin E, Milanfar P. Removal of haze and noise from a single image. Computational Imaging. 2012;82960T. doi: 10.1117/12.906773.
Lan X, Zhang L, Shen H, Yuan Q, Li H. Single image haze removal considering sensor blur and noise. EURASIP journal on advances in signal processing. 2013;1:86. CrossRef
Nan D, Bi DY, Liu C, Ma SP, He LY. A bayesian framework for single image dehazing considering noise. Sci World J. 2014. doi: 10.1155/2014/651986.
Guo W, Qin J, Yin W. A new detail-preserving regularization scheme. SIAM journal on imaging sciences. 2014;7(2):1309–34. CrossRef
Huang SC, Yeh CH. Image contrast enhancement for preserving mean brightness without losing image features. Eng Appl Artif Intell. 2013;26(5):1487–92. CrossRef
Yadav G, Maheshwari S, Agarwal A. Contrast limited adaptive histogram equalization based enhancement for real time video system. 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2014. p. 2392–2397.
Dong L, Feng N, Zhang Q. LSI: latent semantic inference for natural image segmentation. Pattern Recogn. 2016;59:282–91. CrossRef
Shah SAA, Bennamoun M, Boussaid F. Iterative deep learning for image set based face and object recognition. Neurocomputing. 2016;174:866–74.
Li G, Liu ZY, Li HB, Ren P. Target tracking based on biological-like vision identity via improved sparse representation and particle filtering. Cogn Comput. 2016;8(5):910–23. CrossRef
Xiao C, Gan J. Fast image dehazing using guided joint bilateral filter. Vis Comput. 2012;28(6–8):713–21. CrossRef
- Model Based Edge-Preserving and Guided Filter for Real-World Hazy Scenes Visibility Restoration
- Springer US
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