Skip to main content
SpringerLink
Log in

Underwater optical image processing based on double threshold judgements and optimized red dark channel prior method

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Underwater images are prone to suffer from color distortion and low visibility because of the strong light attenuation. The traditional dark channel prior (DCP) method tends to fail when used for underwater image restoration. By exploring the differences in light attenuation between atmosphere and water, we propose an innovative image restoration method—optimized red dark channel prior (ORDCP) which adds a valid contrast indicator. In addition, we set double threshold judgments to determine the main color tone and calculate red channel transmission map. After getting the two estimated parameters including transmission maps and background light, we can restore underwater images using conventional underwater imaging model. The subjective evaluations indicate that the algorithm we proposed has better performance in terms of saturation, contrast and images edge details. What’s more, the results of objective evaluation metrics show that the performances maximally increase by 32.32% in underwater images such as the ship and stone. The conclusion can be drawn that the proposed method is able to remove the noise and blur caused by complicated underwater environment and performs favorably against the state-of-the-art algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Adrian G, David P, Artzai P, Aitor AG (2015) Automatic Red-Channel underwater image restoration. J Vis Commun Image Represent 26:132–145

    Article  Google Scholar 

  2. Amer KO, Elbouz M, Alfalou A, Brosseau C, Hajjami J (2019) Enhancing underwater optical imaging by using a low-pass polarization filter. Opt Express 27(2):621–643

    Article  Google Scholar 

  3. Buchsbaum G (1980) A spatial processor model for object color perception. J Franklin Inst-Eng Appl Math 310(1):1–26

    Article  Google Scholar 

  4. Chang H (2020) Single underwater image restoration based on adaptive transmission fusion. IEEE Access 86(3):50–62

    Google Scholar 

  5. Chen X, Yu J, Kong S, Wu Z, Fang X, Wen L (2020) Towards Real-Time advancement of underwater visual quality with GAN. IEEE Trans Ind Electron 66(12):50–59

    Google Scholar 

  6. Cheng CY, Sung CC, Chang HH (2015) Underwater image restoration by red-dark channel prior and point spread function deconvolution. presented at 2015 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), pp 110–115

  7. Dai C, Lin M, Wu X, Wang Z, Guan Z (2019) Single underwater image restoration by decomposing curves of attenuating color. Opt Laser Technol:1–11

  8. De Oliveira JF, Duarte GA, Codevilla Moraes F, Drews Jr P, Silvia SCB (2019) Single image restoration for participating media based on prior fusion. IEEE Comput Graph Appl 39(1):71–83

    Article  Google Scholar 

  9. Fattal R (2008) Single image dehazing. ACM Trans Graph 27 (3):721–729

    Article  Google Scholar 

  10. Finlayson GD, Trezzi E (2004) Shades of gray and color constancy. presented at Color Imaging Conference (CIC), Arizona, pp 37–41

  11. Gillis DB (2020) An underwater target detection framework for hyperspectral imagery. IEEE J Sel Top Appl Earth Observ Remote Sens 13:1798–1810

    Article  Google Scholar 

  12. Gordon HR (1989) Dependence of the diffuse reflectance of natural waters on the sun angle. Limnol Oceanogr 34(8):1484–1489

    Article  Google Scholar 

  13. Gould RW, Arnone RA, Martinolich M (1999) Spectral dependence of the scattering coefficient in case 1 and case 2 waters. Appl Opt 38(12):77–83

    Article  Google Scholar 

  14. Guo Q, Xue L, Tang R, Guo L (2017) Underwater image enhancement based on the dark channel prior and attenuation compensation. J Ocean Univ China 16(5):57–65

    Article  Google Scholar 

  15. Han PL, Liu F, Wei Y, et al. (2020) Optical correlation assists to enhance underwater polarization imaging performance. Opt Lasers Eng 134:1–6

    Google Scholar 

  16. He KM, Sun J, Tang XO (2010) Guided image filtering. presented at European Conference on Computer Vision (ECCV), pp 1–14

  17. He KM, Sun J, Tang XO (2011) Single image haze removal using dark channel prior. IEEE Trans Pattern Anal Mach Intell 33(12):2341–2353

    Article  Google Scholar 

  18. Hou G, Li J, Wang G, Pan Z, Zhao X (2020) Underwater image dehazing and denoising via curvature variation regularization. Multimed Tools Appl:1–21

  19. Hou G, Li J, Wang G, Yang H, Huang B, Pan Z (2019) A novel dark channel prior guided variational framework for underwater image restoration. J Vis Commun Image Represent:1–25

  20. Jaffe JS (1990) Computer modeling and the design of optimal underwater imaging systems. IEEE J Ocean Eng 15(2):101–111

    Article  Google Scholar 

  21. Joel D.O, Gaya FC, Duarte AC, Botelho S (2016) General Participative Media Single Image Restoration. https://researchgate.net/publcatlon/301842046

  22. Liu YZ, Chi KC, Lin S (2020) Underwater image restoration based on background light estimation and transmittance optimization. Laser Optoelectron:1–14

  23. Luo Y, Qin J, Xiang X, Tan Y, Liu Q, Xiang LY (2020) Coverless real-time image information hiding based on image block matching and dense convolutional network. J Real-Time Image Proc 17:125–135

    Article  Google Scholar 

  24. Łuczyński T, Birk A (2018) Underwater Image Haze Removal and Color Correction with an Underwater-ready Dark Channel Prior. IEEE Oceans 1:1–8

    Google Scholar 

  25. Ma XM, Chen ZH, Feng ZP (2019) Underwater image restoration through a combination of improved dark channel prior and gray world algorithms. J Electron Imaging 28(5):1–10

    Article  Google Scholar 

  26. Mathias A, Samiappan D (2019) Underwater Image Restoration based on Diffraction Bounded Optimization Algorithm with Dark Channel Prior. Optik 19(2):1–8

    Google Scholar 

  27. Nakatani T, Yoshida H, Hyakudome T et al (2013) Dives of cruising-AUV “JINBEI” to methane hydrate area on Joetsu knoll and Umitaka Spur, 2013 OCEANS, San Diego, pp 1–5

  28. Panetta K, Gao C, Agaian S (2016) Human-Visual-System-Inspired Underwater image quality measures. IEEE J Ocean Eng 41(3):541–551

    Article  Google Scholar 

  29. Perez J, Bryson M, Williams SB, Sanz PJ (2020) Recovering depth from still images for underwater dehazing using deep learning. Sensors 20(16):1–16

    Article  Google Scholar 

  30. Song W, Wang Y, Huang D, Liotta A, Perra C (2020) Enhancement of underwater images with statistical model of background light and optimization of transmission map. IEEE Trans Broadcast 66(1):153–169

    Article  Google Scholar 

  31. Tang ZQ, Zhou B, Dai XZ, Gu HT (2018) Vision enhancement of underwater vehicle based on improved DCP algorithm. Robot 40(2):222–230

    Google Scholar 

  32. Xu H, Tan Y, Wang W, Wang G (2020) Image dehazing by incorporating markov random field with dark channel prior. J Ocean Univ China 19 (3):551–560

    Article  Google Scholar 

  33. Yang S, Chen Z, Feng Z, Ma X (2020) Underwater image enhancement using scene Depth-Based adaptive background light estimation and dark channel prior algorithms. IEEE Access 1(3):318–327

    Google Scholar 

  34. Yang AP, Qu C, Wang J (2018) Image sharpening algorithm based on underwater imaging model. J Electron Inf Technol 40(2):298–305

    Google Scholar 

  35. Yang M, Sowmya A (2015) An underwater color image quality evaluation metric. IEEE Trans Image Process 24(12):62–71

    MathSciNet  MATH  Google Scholar 

  36. Yang M, Sowmya A, Wei Z, Zheng B (2020) Offshore underwater image restoration using Reflection-Decomposition-Based transmission map estimation. IEEE J Ocean Eng 45(2):521–533

    Article  Google Scholar 

  37. Yu H, Li X, Lou Q, Lei C, Liu Z (2020) Underwater image enhancement based on DCP and depth transmission map. Multimed Tools Appl:1–48

  38. Zhang S, Gong X, Nian R, He B, Wang Y, Lendasse A (2017) A depth estimation model from a single underwater image with non-uniform illumination correction. presented at OCEANS 2017 – Aberdeen, pp 1–5

  39. Zhao XW, Jin T, Qu S (2015) Deriving inherent optical properties from background color and underwater image enhancement. Ocean Eng 94:163–172

    Article  Google Scholar 

Download references

Acknowledgements

The research work is supported by the The National Natural Science Foundation of China(61801270), The National Natural Science Foundation of China (61471224) and Shandong Province Key R&D Program (Public Welfare Project) (2018GHY115022). Many thanks to the anonymous reviewers for their constructive comments and valuable suggestions.

Author information

Authors and Affiliations

  1. College of Electronic Information Engineering, Shandong University of Science and Technology, Qingdao, China

    Qi Wu, YinJing Guo, JiaChen Hou, JiaoJiao Yuan, Fang Kong, Zhen Liu, WenJian Yang & QuanQuan Liang

  2. College of Transportation, Shandong University of Science and Technology, Qingdao, China

    WenHong Lyu

Authors
  1. Qi Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. YinJing Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. JiaChen Hou
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. JiaoJiao Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Fang Kong
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. WenHong Lyu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Zhen Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. WenJian Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. QuanQuan Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to YinJing Guo.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, Q., Guo, Y., Hou, J. et al. Underwater optical image processing based on double threshold judgements and optimized red dark channel prior method. Multimed Tools Appl 80, 29985–30002 (2021). https://doi.org/10.1007/s11042-021-11200-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-021-11200-8

Keywords

Search

Navigation