Skip to main content

The Autonomous Underwater Vehicle Vision Denoising Method of Surfacelet Based on Sample Matrix

  • Conference paper
Intelligent Robotics and Applications (ICIRA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5314))

Included in the following conference series:

Abstract

Through analyzing needs of the autonomous underwater vehicle vision, the autonomous underwater vehicle vision denosing method of Surfacelet based on sample matrix is proposed. N nosing image are produced by one image adding noise based on N sample matrix, which are circle shifted respectively and constructed image sequence. The image sequence is implemented Surfacelet transform and employed the hard thresholding denoising to coefficient and then linear average in airspace. The experimental results indicate that image de-noised has not Gibbs—like phenomena of Wavelet and nick effect. The method can restrain noise to underwater sonar image and hold detail and texture of image to target fringe of noise distribute strongly. The method has important significance to autonomous underwater vehicle planning for safe navigation routes and successful completion of the tasks.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ye, L., Wen-tian, C., Tie-dong, Z.: Underwater vehicle local path planning based on sonar image processing. Journal of Harbin Engineering University 27, 358–361 (2006) (in Chinese)

    Google Scholar 

  2. Zhuo-fu, L., En-fang, S.: Sonar image recognition in wavelet domain. Journal of Harbin Engineering University 24, 495–499 (2003) (in Chinese)

    Google Scholar 

  3. Ya-an, L., Hong-chao, W., Jing, C.: Research of noise reduction of underwater acoustic signals based on singular spectrum analysis. J. Systems Engineering and Electronics 29, 524–527 (2007) (in Chinese)

    Google Scholar 

  4. Enfang, S., Zhuofu, L.: Underwater acoustic image segmentation based on deformable template. J. Acta Acustica 30, 363–366 (2005) (in Chinese)

    Google Scholar 

  5. Do, M.N., Vetterli, M.: The Contourlet Transform.: An Efficient Directional Multiresolution Image Representation. J. IEEE Transactions on Image Processing 14, 2091–2106 (2005)

    Article  MathSciNet  Google Scholar 

  6. Lu, K.Y., Do, M.N.: 3-D directional filter banks and Surfacelets. In: Proceeding of SPIE conference on Wavelet Applications in Signal and Image Processing XI. The International Society for Optical Engineering, San Diego, USA, pp. 591–601 (2005)

    Google Scholar 

  7. Lu, K.Y., Do, M.N.: Video processing using the 3-dimensional surfacelet transform. In: Fortieth Annual Asilomar Conference on Signals, Systems and Computers, pp. 883–887. Pacific Grove, CA (2006)

    Chapter  Google Scholar 

  8. Lu, Y., Do, M.N.: Multidimensional Directional Filter Banks and Surfacelets. J. IEEE Transactions on Image Processing 16, 918–931 (2007)

    Article  MathSciNet  Google Scholar 

  9. Lu, Y., Do, M.N.: A new contourlet transform with sharp frequency localization. In: Proc. IEEE Int. Conf. on Image Proc., Atlanta, USA, October 2006, pp. 1629–1632 (2006)

    Google Scholar 

  10. Hailan, Z., Wen, X., Weiqing, Z.: A study on the statistics of sonic images. J. Acta Acustica 16, 381–387 (1991) (in Chinese)

    Google Scholar 

  11. Cunha, A.L., Zhou, J., Do, M.N.: The nonsubsampled contourlet transform: Theory, design, and applications. J. IEEE Transactions on Image Processing 15, 3089–3101 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Liu, Dd. (2008). The Autonomous Underwater Vehicle Vision Denoising Method of Surfacelet Based on Sample Matrix. In: Xiong, C., Huang, Y., Xiong, Y., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2008. Lecture Notes in Computer Science(), vol 5314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88513-9_83

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-88513-9_83

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88512-2

  • Online ISBN: 978-3-540-88513-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics