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Shallow-Water Image Enhancement Using Relative Global Histogram Stretching Based on Adaptive Parameter Acquisition

  • Dongmei Huang
  • Yan Wang
  • Wei SongEmail author
  • Jean Sequeira
  • Sébastien Mavromatis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10704)

Abstract

Light absorption and scattering lead to underwater image showing low contrast, fuzzy, and color cast. To solve these problems presented in various shallow-water images, we propose a simple but effective shallow-water image enhancement method - relative global histogram stretching (RGHS) based on adaptive parameter acquisition. The proposed method consists of two parts: contrast correction and color correction. The contrast correction in RGB color space firstly equalizes G and B channels and then re-distributes each R-G-B channel histogram with dynamic parameters that relate to the intensity distribution of original image and wavelength attenuation of different colors under the water. The bilateral filtering is used to eliminate the effect of noise while still preserving valuable details of the shallow-water image and even enhancing local information of the image. The color correction is performed by stretching the ‘L’ component and modifying ‘a’ and ‘b’ components in CIE-Lab color space. Experimental results demonstrate that the proposed method can achieve better perceptual quality, higher image information entropy, and less noise, compared to the state-of-the-art underwater image enhancement methods.

Keywords

Shallow-water image enhancement Relative global histogram stretching (RGHS) Adaptive parameter acquisition 

Notes

Acknowledgment

This work was supported by the Program for Professor of Special Appointment (Eastern Scholar at Shanghai Institutions of Higher Learning No. TP2016038, the National Natural Science Foundation of China (NSFC) Grant 61702323, and the Doctoral Research Startup Fund of Shanghai Ocean University A2-0203-17-100322.

References

  1. 1.
    Sahu, P., Gupta, N., Sharma, N.: A survey on underwater image enhancement techniques. Int. J. Comput. Appl. 87(13), 19–23 (2014)Google Scholar
  2. 2.
    Zaneveld, J.R.V., Pegau, W.S.: Robust underwater visibility parameter. Opt. Express 11(23), 2997–3009 (2003)CrossRefGoogle Scholar
  3. 3.
    Schettini, R., Corchs, S.: Underwater image processing: state of the art of restoration and image enhancement methods. EURASIP J. Adv. Sig. Process. 2010(1), 746052 (2010)CrossRefGoogle Scholar
  4. 4.
    Zhao, X., Jin, T., Qu, S.: Deriving inherent optical properties from background color and underwater image enhancement. Ocean Eng. 94, 163–172 (2015)CrossRefGoogle Scholar
  5. 5.
    He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. IEEE Trans. Pattern Anal. Mach. Intell. 33(12), 2341–2353 (2011)CrossRefGoogle Scholar
  6. 6.
    Galdran, A., Pardo, D., Picón, A., Alvarez-Gila, A.: Automatic red-channel underwater image restoration. J. Vis. Commun. Image Represent. 26, 132–145 (2015)CrossRefGoogle Scholar
  7. 7.
    Drews, P., Nascimento, E., Moraes, F., Botelho, S., Campos, M.: Transmission estimation in underwater single images. In: Proceedings of IEEE ICCVW 2013, pp. 825–830 (2013)Google Scholar
  8. 8.
    Chiang, J.Y., Chen, Y.C.: Underwater image enhancement by wavelength compensation and dehazing. IEEE Trans. Image Process. 21(4), 1756–1769 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Iqbal, K., Abdul Salam, R., Osman, M.A., Talib, A.Z.: Underwater image enhancement using an integrated colour model. IAENG Int. J. Comput. Sci. 32(2), 239–244 (2007)Google Scholar
  10. 10.
    Iqbal, K., Odetayo, M., James, A., Salam, R.A., Talib, A.Z.H.: Enhancing the low quality images using unsupervised colour correction method. In: 2010 IEEE International Conference on Systems, Man and Cybernetics, pp. 1703–1709 (2010)Google Scholar
  11. 11.
    Ghani, A.S.A., Isa, N.A.M.: Underwater image quality enhancement through integrated color model with Rayleigh distribution. Appl. Soft Comput. 27, 219–230 (2015)CrossRefGoogle Scholar
  12. 12.
    Schechner, Y.Y., Karpel, N.: Recovery of underwater visibility and structure by polarization analysis. IEEE J. Ocean. Eng. 30(3), 570–587 (2005)CrossRefGoogle Scholar
  13. 13.
    Yang, M., Sowmya, A.: An underwater color image quality evaluation metric. IEEE Trans. Image Process. 24(12), 6062–6071 (2015)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Mantiuk, R., Kim, K.J., Rempel, A.G., Heidrich, W.: HDR-VDP-2: a calibrated visual metric for visibility and quality predictions in all luminance conditions. In: ACM SIGGRAPH 2011 Papers, New York, NY, USA, vol. 40, pp. 1–14 (2011)Google Scholar
  15. 15.
    Hitam, M.S., Awalludin, E.A., Yussof, W.N.J.H.W., Bachok, Z.: Mixture contrast limited adaptive histogram equalization for underwater image enhancement. In: 2013 International Conference on Computer Applications Technology (ICCAT), pp. 1–5 (2013)Google Scholar
  16. 16.
    Schechner, Y.Y., Narasimhan, S.G., Nayar, S.K.: Instant dehazing of images using polarization. In: Proceedings of 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 325–332 (2001)Google Scholar
  17. 17.
    Narasimhan, S.G., Nayar, S.K.: Vision and the atmosphere. Int. J. Comput. Vis. 48(3), 233–254 (2002)CrossRefzbMATHGoogle Scholar
  18. 18.
    Ghani, A.S.A., Isa, N.A.M.: Underwater image quality enhancement through Rayleigh-stretching and averaging image planes. Int. J. Nav. Archit. Ocean Eng. 6(4), 840–866 (2014)CrossRefGoogle Scholar
  19. 19.
    Ghani, A.S.A., Isa, N.A.M.: Enhancement of low quality underwater image through integrated global and local contrast correction. Appl. Soft Comput. 37, 332–344 (2015)CrossRefGoogle Scholar
  20. 20.
    Paris, S., Durand, F.: A fast approximation of the bilateral filter using a signal processing approach. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3954, pp. 568–580. Springer, Heidelberg (2006).  https://doi.org/10.1007/11744085_44 CrossRefGoogle Scholar
  21. 21.
    Chambah, M., Semani, D., Renouf, A., Courtellemont, P., Rizzi, A.: Underwater color constancy: enhancement of automatic live fish recognition. In: Color Imaging IX: Processing, Hardcopy, and Applications, vol. 5293, pp. 157–168 (2003)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Dongmei Huang
    • 1
  • Yan Wang
    • 1
  • Wei Song
    • 1
    Email author
  • Jean Sequeira
    • 2
  • Sébastien Mavromatis
    • 2
  1. 1.College of Information TechnologyShanghai Ocean UniversityShanghaiChina
  2. 2.Aix-Marseille UniversityMarseilleFrance

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