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Czasopismo
2018 | Vol. 48, nr 3 | 515--527
Tytuł artykułu

A fast dehazing method with high color fidelity

Autorzy
Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper, we present a fog image degradation model with the combination of HSI color space and the atmosphere scattering model. Based on the model, a fast dehazing method with high color fidelity has been proposed. The main advantage of the proposed method compared with others is its speed. This speed allows the method to be applied within real-time processing applications as a step of preprocessing. Another advantage is the possibility to handle both color images and gray level images. The algorithm depends only on on two parameters, and both are easy to set. Experiments on haze images demonstrate that the proposed method can achieve wonderful image visibility with a higher computing speed.
Wydawca

Czasopismo
Rocznik
Strony
515--527
Opis fizyczny
Bibliogr. 13 poz., rys., tab.
Twórcy
autor
  • Engineering Research Center for Optoelectronics of Guangdong Province, School of Physics and Optoelectronics, South China University of Technology, Guangzhou 510640, China
  • Guangdong Provincial Key Laboratory of Precision Equipment and Manufacturing Technology, mSchool of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, 510640, China
autor
  • Engineering Research Center for Optoelectronics of Guangdong Province, School of Physics and Optoelectronics, South China University of Technology, Guangzhou 510640, China
Bibliografia
  • [1] NARASIMHAN S.G., NAYAR S.K., Chromatic framework for vision in bad weather, Proceedings IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2000, Vol. 1, 2000, pp. 598–605.
  • [2] NARASIMHAN S.G., NAYAR S.K., Contrast restoration of weather degraded images, IEEE Transactions on Pattern Analysis and Machine Intelligence 25(6), 2003, pp. 713–724.
  • [3] NAYAR S.K., NARASIMHAN S.G., Vision in bad weather, Proceedings of the Seventh IEEE International Conference on Computer Vision, Vol. 2, 1999, pp. 820–827.
  • [4] SCHECHNER Y.Y., NARASIMHAN S.G., NAYAR S.K., Instant dehazing of images using polarization, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, Vol. 1, 2001, pp. I-325–I-332.
  • [5] SHWARTZ S., NAMER E., SCHECHNER Y.Y., Blind haze separation, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR ‘06), Vol. 2, 2006, pp. 1984–1991.
  • [6] MUDGE J., VIRGEN M., Real time polarimetric dehazing, Applied Optics 52(9), 2013, pp. 1932–1938.
  • [7] SHUYIN TAO, HUAJUN FENG, ZHIHAI XU, QI LI, Image degradation and recovery based on multiple scattering in remote sensing and bad weather condition, Optics Express 20(15), 2012, pp. 16584–16595.
  • [8] CHIA-HUNG YEH, LI-WEI KANG, MING-SUI LEE, CHENG-YANG LIN, Haze effect removal from image via haze density estimation in optical model, Optics Express 21(22), 2013, pp. 27127–27141.
  • [9] FATTAL R., Single image dehazing, ACM Transactions on Graphics (TOG) 72(3), 2008, article ID 27.
  • [10] TAN R.T., Visibility in bad weather from a single image, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008, pp. 1–8.
  • [11] KAIMING HE, JIAN SUN, XIAOOU TANG, Single image haze removal using dark channel prior, IEEE Transactions on Pattern Analysis and Machine Intelligence 33(12), 2011, pp. 2341–2353.
  • [12] KAIMING HE, JIAN SUN, XIAOOU TANG, Guided image filtering, [In] Computer Vision – ECCV 2010. Lecture Notes in Computer Science, [Eds.] K. Daniilidis, P. Maragos, N. Paragios, Vol. 6311, Springer, Berlin, Heidelberg, 2010, pp. 1–14.
  • [13] YANGYANG XIANG, SAHAY R.R., KANKANHALLI M.S., Hazy image enhancement based on the full-saturation assumption, 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 2013, pp. 1–4.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-16ff9080-937e-4a77-af6a-fdbbdd1faf83
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