IEIE Transactions on Smart Processing and Computing

The Institute of Electronics and Information Engineers (대한전자공학회)
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A Novel Imaging System for Removal of Underwater Distortion using Code V

  • Maik, Vivek (Department of Electronics and Communication, The Oxford College of Engineering) ;
  • Daniel, Stella (Department of Electronics and Communication, The Oxford College of Engineering) ;
  • Chrispin Jiji, A. (Department of Electronics and Communication, The Oxford College of Engineering)
  • Received : 2017.01.03
  • Accepted : 2017.03.24
  • Published : 2017.06.30
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Abstract

Images obtained from underwater are usually degraded due to the environmental conditions. Some of the typical degradation factors include turbidity and color degradation. These degradations can be attributed to the absorptive and scattering properties of underwater degradation in terms of optical parameters, such as modulation transfer function (MTF), optical transfer function (OTF),point spread function (PSF), and color constancy. In this paper, we use the CODE V optical simulation software to mimic underwater conditions and model the imaging platform, thereby studying various parameters, such as PSF and MTF, and we use the PSF to remove the underwater turbidity. Experimental results show increased performance with the algorithm, compared to other existing methods.

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References

  1. B. McGlamery, "A computer model for underwater camerasystem," in Ocean Optics VI, S. Q. Duntley, Ed., vol. 208 of Proceedings of SPIE, pp. 221-231, 1979.
  2. J. S. Jaffe, "Computer modeling and the design of optimal underwater imaging systems," IEEE Journal of Oceanic Engineering, vol. 15, no. 2, pp. 101-111, 1990. https://doi.org/10.1109/48.50695
  3. C. Funk, S. Bryant, and P. Heckman, "Handbook of underwater imaging system design," Tech. Rep. TP303, Naval Undersea Center, San Diego, Calif, USA, 1972.
  4. T. H. Dixon, T. J. Pivirotto, R. F. Chapman, and R. C. Tyce, "A range-gated laser system for ocean floor imaging," Marine Technology Society Journal, vol. 17, 1983.
  5. J.McLean and K. Voss, "Point spread functions in ocean water: comparison between theory and experiment," Applied Optics, vol. 30, pp. 2027-2030, 1991. https://doi.org/10.1364/AO.30.002027
  6. K. Voss, "Simple empirical model of the oceanic point spread function," Applied Optics, vol. 30, pp. 2647-2651, 1991. https://doi.org/10.1364/AO.30.002647
  7. J. Jaffe, K. Moore, J. McLean, and M. Strand, "Under water optical imaging: status and prospects," Oceanography, vol. 14,pp. 66-76, 2001.
  8. J. Mertens and F. Replogle, "Use of point spread and beam spread functions for analysis of imaging systems in water," Journal of the Optical Society of America, vol. 67, pp. 1105-1117, 1977. https://doi.org/10.1364/JOSA.67.001105
  9. W. Hou, D. J. Gray, A. D. Weidemann, G. R. Fournier, andJ. L. Forand, "Automated underwater image restoration and retrieval of related optical properties," in Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS '07), pp. 1889-1892, 2007.
  10. W. Hou, A. D. Weidemann, D. J. Gray, and G. R. Fournier, "Imagery-derived modulation transfer function and its applications for underwater imaging," in Applications of Digital Image Processing, vol. 6696 of Proceedings of SPIE, San Diego, Calif, USA, August 2007
  11. Bartolini, L., De Dominicis, M., Ferri de Collibus, G., Fornetti, M., Guarneri, E., Paglia, C.P. and Ricci, R. 2005. Underwater three-dimensional imaging with an amplitude- modulated laser radar at a 405 nm wavelength. Appl Opt. 44:7130-7135. https://doi.org/10.1364/AO.44.007130
  12. Baumgartner, L., Reynoldson, N., Cameron, L. and Stanger, J. 2006. Application of a dual-frequency identification sonar (DIDSON) to fish migration studies.
  13. In: Lyle, J.M., Furlani, D.M. and Buxton, C.D., eds. Cutting-edge technologies in fisheries science. Australian SocForProc Fish Biology Wkshp Proc., 91-98.
  14. Benzie, P.W., Watson, J., Burns, N., Sun, H.Y. 2007a. Developments for underwater remote vision. IEEE 3DTV Conference, Kos, Greece, 1-4.
  15. Blevins, E. and Johnsen, S. 2004. Spatial vision in the echinoid genus Echinometra. J Exp Biol. 207:4249-4253. https://doi.org/10.1242/jeb.01286
  16. RaimanodoSchettini and Silvia Corchs "Underwater Image Processing: State of the Art of Restoration and Image Enhancement Methods", EURASIP Journal on Advances in Signal Processing,2010.
  17. Code V reference manual.
  18. Z.Liu, Y.Yu, K.Zhang and H.Huang, "underwater image transmission and blurred image restoration," opticalEngineering, vol.40,no6, pp 1125-1131,2001. https://doi.org/10.1117/1.1364500
  19. B. McGlamery, "A computer model for underwater camera system," in Ocean Optics VI, S. Q. Duntley, Ed., vol. 208 of Proceedings of SPIE, pp. 221-231, 1979.
  20. Mauricio Delbracio, Publo Muse , Andres Almansa "Non -parametric Sub - Pixel Local Point Spread Function Estimation," Image Processing online, 2012.
  21. Y. Y. Schechner and N. Karpel, "Recovery of underwater visibility and structure by polarization analysis," IEEE Journal of Oceanic Engineering, vol. 30, no. 3, pp. 570-587, 2005. https://doi.org/10.1109/JOE.2005.850871