Abstract
Due to the effect of sea wave, the image captured by the camera underwater is not clear and the distortion. In order to pave the way for image correction and take corresponding measures to reconstruct the sea surface on the whole hemisphere image. This paper introduces the principle of Snell cone, analysis the principle of underwater imaging and proposes a method that along the Snell cone boundary element wave scattering calculation, obtain satisfies the linearized dynamic equations of wave height estimation, light path vector and fitting the whole image sequence, to estimate the wave ray tracing based on reverse. Furthermore, optical system model is built, and the light path through the air wave image generation is simulated by MATLAB. The simulation results show that, it can be used as a reference for the image distortion reduction of underwater imaging system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alterman, M., Schechner, Y.Y., Swirski, Y.: Triangulation in random refractive distortions. In: IEEE International Conference on Computational Photography, pp. 1–10. IEEE (2013)
Suiter, H., Flacco, N., Carter, P., et al.: Optics near the snell angle in a water-to-air change of medium. In: Oceans, pp. 1–12. IEEE (2007)
Alterman, M., Swirski, Y., Schechner, Y.Y.: STELLA MARIS: Stellar marine refractive imaging sensor. In: IEEE International Conference on Computational Photography, pp. 1–10. IEEE (2014)
Schultz, H., Corrada-Emmanuel, A.: System and method for imaging through an irregular water surface: US, US7630077 (2009)
Levin, I.M., Savchenko, V.V., Osadchy, V.J.: Correction of an image distorted by a wavy water surface: laboratory experiment. Appl. Opt. 47(35), 6650–6655 (2008)
Tian, Y., Narasimhan, S.G.: Seeing through water: Image restoration using model-based tracking. In: IEEE International Conference on Computer Vision, pp. 2303–2310. IEEE (2009)
Swirski, Y., Schechner, Y.Y., Herzberg, B., et al.: Stereo from flickering caustics. In: IEEE International Conference on Computer Vision, pp. 205–212. IEEE (2009)
Swirski, Y., Schechner, Y.Y., Herzberg, B., et al.: CauStereo: range from light in nature. Appl. Opt. 50(28), F89 (2011)
Swirski, Y., Schechner, Y.Y., Nir, T.: Variational stereo in dynamic illumination. In: IEEE International Conference on Computer Vision, pp. 1124–1131. IEEE (2011)
Gracias, N., Negahdaripour, S., Neumann, L., et al.: A motion compensated filtering approach to remove sunlight flicker in shallow water images. In: Oceans 2008, pp. 1–7. IEEE
Liu, Y., Su, M., Yan, X., Liu, W.: The mean-square slope of ocean waves and its effects on radar backscatter. J. Atmos. Oceanic Technol. 17, 1092–1105 (2000)
Kocak, D.M., Dalgleish, F.R., Caimi, F.M., et al.: A focus on recent developments and trends in underwater imaging. Mar. Technol. Soc. J. 42(1), 52–67 (2008)
Schechner, Y.Y., Karpel, N.: Recovery of underwater visibility and structure by polarization analysis. IEEE J. Oceanic Eng. 30(3), 570–587 (2005)
Brox, T., Bruhn, A., Papenberg, N., et al.: High accuracy optical flow estimation based on a theory for warping, vol. 3024, pp. 25–36 (2004)
Molkov, A.A., Dolin, L.S.: Determination of wind roughness characteristics based on an underwater image of the sea surface. Izv. Atmos. Oceanic Phys. 48(5), 552–564 (2012)
Dolin, L.S., Luchinin, A.G., Titov, V.I., et al.: Correcting images of underwater objects distorted by sea surface roughness. In: Current Research on Remote Sensing, Laser Probing, and Imagery in Natural Waters, p. 66150K. International Society for Optics and Photonics (2007)
Carter, P.W.: Reconstruction of through-surface underwater imagery. Waves Random Complex Media 16(4), 521–530 (2006)
Schechner, Y.Y.: A view through the waves. Mar. Technol. Soc. J. 47(5), 148–150 (2013)
Acknowledgement
This work was supported in part by the National Natural Science Foundation of China (No. 61673129, 51674109) and the Harbin Application Research Funds (2016RQQXJ096).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Cai, C., Zheng, J., Liang, Y. (2018). Simulation of Upward Underwater Image Distortion Correction. In: Barolli, L., Terzo, O. (eds) Complex, Intelligent, and Software Intensive Systems. CISIS 2017. Advances in Intelligent Systems and Computing, vol 611. Springer, Cham. https://doi.org/10.1007/978-3-319-61566-0_89
Download citation
DOI: https://doi.org/10.1007/978-3-319-61566-0_89
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-61565-3
Online ISBN: 978-3-319-61566-0
eBook Packages: EngineeringEngineering (R0)