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Reseach Article

Haze Removal and Color Compensation of Underwater Image

by Nisha Kumari, Ramesh Kumar Sunkaria
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 6
Year of Publication: 2013
Authors: Nisha Kumari, Ramesh Kumar Sunkaria
10.5120/11583-6915

Nisha Kumari, Ramesh Kumar Sunkaria . Haze Removal and Color Compensation of Underwater Image. International Journal of Computer Applications. 68, 6 ( April 2013), 15-20. DOI=10.5120/11583-6915

@article{ 10.5120/11583-6915,
author = { Nisha Kumari, Ramesh Kumar Sunkaria },
title = { Haze Removal and Color Compensation of Underwater Image },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 6 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 15-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number6/11583-6915/ },
doi = { 10.5120/11583-6915 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:27:05.952698+05:30
%A Nisha Kumari
%A Ramesh Kumar Sunkaria
%T Haze Removal and Color Compensation of Underwater Image
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 6
%P 15-20
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In underwater image capturing, color change and presence of haze are the two sources of distortion. These distortions are caused by light scattering and light attenuation occurred by light traveling in water with different wavelengths. These changes are caused by light incident on objects, reflected and deflected by different particles present in the propagation path before reaching the camera. Thus the images are hazy and have bluish tone. In the present work, haze removing technique proposed to enhance the image and to compensate the other colors which have disappeared. In the present work, the distortion caused by artificial light, haze effect and appearance of bluish tone are compensated. Based on the amount of attenuation corresponding to each wavelength, color change compensation is conducted and color balance is restored. Effect of noise is also reduced by using the spatial filter. Using this technique the visibility and color of the image can be enhanced.

References
  1. Prabhakar C. J. , and Praveen kumar P. U. , "An image based technique for enhancement of underwater images" IJMI vol. 3, Issue 4, 2011, pp-217-224.
  2. K. Lebart, C. Smith, E. Trucco, and D. M. Lane, "Automatic indexing of underwater survey video: algorithm and benchmarking method," IEEE J. Ocean. Eng. , vol. 28, no. 4, pp. 673–686, Oct. 2003.
  3. J. Yuh and M. West, "Underwater robotics," Adv. Robot. , vol. 15, no. 5, pp. 609–639, 2001.
  4. J. R. Zaneveld and W. Pegau, "Robust underwater visibility parameter," Opt. Exp. , vol. 11, no. 23, pp. 2997–3009, 2003.
  5. E. Trucco and A. T. Olmos-Antillon, "Self-tuning underwater image restoration," IEEE J. Ocean. Eng. , vol. 31, no. 2, pp. 511–519, Apr. 2006.
  6. J. S. Jaffe, "Computer modeling and the design of optimal underwater imaging systems," IEEE J. Ocean. Eng. , vol. 15, no. 2, pp. 101–111, Apr. 1990.
  7. M. C. W. van Rossum and T. M. Nieuwenhuizen, "Multiple scattering of classical waves: Microscopy, mesoscopy and diffusion," Rev. Modern Phys. , vol. 71, no. 1, pp. 313–371, Jan. 1999.
  8. Y. Y. Schechner and N. Karpel, "Recovery of underwater visibility and structure by polarization analysis," IEEE J. Ocean. Eng. , vol. 30, no. 3, pp. 570–587, Jul. 2005.
  9. L. Chao and M. Wang, "Removal of water scattering," in Proc. Int. Conf. Comput. Eng. Technol. , 2010, vol. 2, pp. 35–39.
  10. W. Hou,D. J. Gray,A. D. Weidemann,G. R. Fournier, and J. L. Forand,"Automated underwater image restoration and retrieval of related opticalproperties," in Proc. IGARSS, 2007, vol. 1, pp. 1889–1892.
  11. A. Yamashita, M. Fujii, and T. Kaneko, "Color registration of underwaterimage for underwater sensing with consideration of light attenuation,"in Proc. Int. Conf. Robot. Autom. , 2007, pp. 4570–4575. K.
  12. Iqbal, R. Abdul Salam, A. Osman, and A. Zawawi Talib, "Underwaterimage enhancement using an integrated color model," Int. J. Comput. Sci. , vol. 34, no. 2, pp. 2–12, 2007.
  13. I. Vasilescu, C. Detwiler, and D. Rus, "Color-accurate underwater imaging using perceptual adaptive illumination," in Proc. Robot. Sci. Syst. , Zaragoza, Spain, 2010.
  14. K. He, J. Sun, and X. Tang, "Single image haze removal using DarkChannel Prior," in Proc. IEEE CVPR, 2009, vol. 1, pp. 1956–1963.
  15. S. Shwartz, E. Namer, and Y. Y. Schechner, "Blind haze separation," in Proc. IEEE CVPR, 2006, vol. 2, pp. 1984–1991
  16. . J. T. Houghton, The Physics of Atmospheres, 2nd ed. Cambridge, U. K. : Cambridge Univ. Press, 2001, ch. 2.
  17. W. N. McFarland, "Light in the sea—Correlations with behaviorsof fishes and invertebrates," Amer. Sci. Zoology, vol. 26, no. 2, pp. 389–401, 1986.
  18. S. Q. Duntley, "Light in the sea," J. Opt. Soc. Amer. , vol. 53, no. 2, pp. 214–233, 1963.
  19. John Y. Chiang and Ying-Ching Chen, "Underwater image enhancement by wavelength compensation and image dehazing" in Proc. IEEE J. on IP, vol. 21, no. 4, april 2012.
  20. Y. H. Lee and S. B. Rhee, "Wavelet-based image denoising with optimal filter" on International Journal of information processing system, vol. 1,2005.
  21. [Online]. Available: http://www. youtube. com/user/bubblevision.
  22. R. Fattal, "Single image dehazing," in Proc. Int. Conf. Comput. Graph. Interact. Tech. , 2008, pp. 1–9.
Index Terms

Computer Science
Information Sciences

Keywords

Color compensation denoising light attenuation light scattering haze