Advertisement

Threshold-Dependent Joint Bilateral Filter Algorithm for Enhancing 3D Gated Range-Intensity Correlation Imaging

  • Yuqing Yang
  • Xinwei WangEmail author
  • Liang Sun
  • Jianan Chen
  • Han Dong
  • Minmin Wang
  • Shaomeng Wang
  • Yan Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11741)

Abstract

Three-dimensional gated range-intensity correlation imaging (GRICI) can acquire three-dimensional information of targets with high range resolution in real time. In practical applications, the intensity distribution of laser illumination, light propagation property and target optical reflectivity lead to data holes for 3D images. In this paper, we proposed an improved threshold-dependent joint bilateral filter (TJBF) algorithm based on the characteristics of 3D GRICI to fill data holes and reduce noise. In our method, the composite intensity image obtained by adding two overlapped gate images is used as the gray-domain guidance image for the joint bilateral filter of 3D images. The threshold of 3D reconstruction is used to determine the pixels to be filled and the calculation weight to ensure the accuracy of filling holes and denoising. Experiments show that the holes of 3D images are effectively filled, the whole 3D image is smooth and target edges are clear, and the range resolution is improved after repaired. The research is beneficial for enhancing 3D GRICI in applications of underwater imaging and 3D measurement.

Keywords

Three-dimensional imaging Gated range-intensity correlation imaging Joint bilateral filtering Filling holes 

Notes

Acknowledgements

The authors acknowledge the financial funding of this work by the National Natural Science Foundation of China (NSFC) (Grant 61875189),, the National Key Research and Development Program of China (Grant 2016YFC0500103 and 2016YFC0302503), the Strategic Priority Program of the Chinese Academy of Sciences (No. XDC03060102), and the Youth Innovation Promotion Association CAS (No. 2017155).

References

  1. 1.
    Laurenzis, M., Christnacher, F., Monnin, D.: Long-range three-dimensional active imaging with superresolution depth mapping. Opt. Lett. 32(21), 3146–3148 (2007)CrossRefGoogle Scholar
  2. 2.
    Christnacher, F., et al.: 3D laser gated viewing from a moving submarine platform. In: Proceedings SPIE, vol. 9250, p. 9250F (2014)Google Scholar
  3. 3.
    Xinwei, W., Youfu, L., Yan, Z.: Triangular-range-intensity profile spatial-correlation method for 3D super-resolution range-gated imaging. Appl. Opt. 52(30), 7399–7406 (2013)CrossRefGoogle Scholar
  4. 4.
    Xinwei, W., et al.: Underwater 3D triangular range-intensity correlation imaging beyond visibility range (invited). Infrared Laser Eng. 47(9), 0903001 (2018)CrossRefGoogle Scholar
  5. 5.
    Busck, J., Heiselberg, H.: Gated viewing and high-accuracy three-dimensional laser radar. Appl. Opt. 43(24), 4705–4710 (2004)CrossRefGoogle Scholar
  6. 6.
    Yang, Q.Q., Wang, L.H., Li, D.X., et al.: Hierarchical joint bilateral filtering for depth post-processing. In: IEEE International Conference on Image and Graphics, pp. 129–134 (2011)Google Scholar
  7. 7.
    Park, J., Kim, I.I., Tai, Y.W., et al.: High quality depth map upsampling for 3D-TOF cameras. In: IEEE International Conference on Computer Vision, pp. 1623–1630 (2011)Google Scholar
  8. 8.
    Matyunin, S., Vatolin, D., Berdnikov, Y., et al.: Temporal filtering for depth maps generated by Kinect depth camera. in: 3DTV Conference, pp. 1–4 (2011)Google Scholar
  9. 9.
    Liu, J., Gong, X., Liu, J.: Gded inpainting and filtering for Kinect depth maps. In: IEEE International Conference on Pattern Recognition, pp. 2055–2058 (2012)Google Scholar
  10. 10.
    Telea, A.: An image inpainting technique based on the fast marching method. J. Graph. Tools 9(1), 23–34 (2004)CrossRefGoogle Scholar
  11. 11.
    Camplani, M., Mantecon, T., Salgado, L.: Accurate depth-color scene modeling for 3D contents generation with low cost depth cameras. In: IEEE International Conference on Image Processing, pp. 1741–1744 (2012)Google Scholar
  12. 12.
    Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: IEEE International Conference on Computer Vision, pp. 839–846 (1998)Google Scholar
  13. 13.
    Petschnigg, G., Szeliski, R., Agrawala, M., et al.: Digital photography with flash and no-flash image pairs. ACM Trans. Graph. 23, 661–672 (2001)Google Scholar
  14. 14.
    Xinwei, W., Youfu, L., Yan, Z.: Multi-pulse time delay integration method for flexible 3D super-resolution range-gated imaging. Opt. Express 23(6), 7820–7831 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Yuqing Yang
    • 1
    • 2
  • Xinwei Wang
    • 1
    • 2
    • 3
    Email author
  • Liang Sun
    • 1
  • Jianan Chen
    • 1
  • Han Dong
    • 1
  • Minmin Wang
    • 1
    • 2
  • Shaomeng Wang
    • 1
    • 2
  • Yan Zhou
    • 1
    • 2
    • 3
  1. 1.Optoelectronic System LaboratoryInstitute of Semiconductors, CASBeijingChina
  2. 2.College of Materials Science and Opto-Electronics TechnologyUniversity of Chinese Academy of SciencesBeijingChina
  3. 3.School of Electronic, Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijingChina

Personalised recommendations