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Chinese Optics Letters

Chinese Optics Letters

| PUBLISHED MONTHLY BY CHINESE LASER PRESS AND DISTRIBUTED BY OSA

  • Vol. 4, Iss. 5 — May. 10, 2006
  • pp: 279–281

Speckle reduction algorithm for laser underwater image based on curvelet transform

Wei Ni, Baolong Guo, Liu Yang, and Peiyan Fei  »View Author Affiliations


Chinese Optics Letters, Vol. 4, Issue 5, pp. 279-281 (2006)


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Abstract

Based on the analysis on the statistical model of speckle noise in laser underwater image, a novel speckle reduction algorithm using curvelet transform is proposed. Logarithmic transform is performed to transform the original multiplicative speckle noise into additive noise. An improved hard thresholding algorithm is applied in curvelet transform domain. The classical Monte-Carlo method is adopted to estimate the statistics of contourlet coefficients for speckle noise, thus determining the optimal threshold set. To further improve the visual quality of despeckling laser image, the cycle spinning technique is also utilized. Experimental results show that the proposed algorithm can achieve better performance than classical wavelet method and maintain more detail information.

© 2006 Chinese Optics Letters

OCIS Codes
(100.2980) Image processing : Image enhancement
(100.7410) Image processing : Wavelets
(110.4280) Imaging systems : Noise in imaging systems
(140.0140) Lasers and laser optics : Lasers and laser optics

Citation
Wei Ni, Baolong Guo, Liu Yang, and Peiyan Fei, "Speckle reduction algorithm for laser underwater image based on curvelet transform," Chin. Opt. Lett. 4, 279-281 (2006)
http://www.opticsinfobase.org/col/abstract.cfm?URI=col-4-5-279


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References

  1. P. Fei, B. Guo, F. Meng, Z. Zhang, and X. Zhang, Chin. J. Lasers (in Chinese) 31, 815 (2004).
  2. E. J. Candes, Ridgelets theory and applications PhD Thesis (Standford University, 1999).
  3. J. C. Dainty, Laser Speckle and Related Phenomena (Springer Press, NY, 1984) chap.1.
  4. B. B. Saevarsson, J. R. Sveinsson, and J. A. Benediktsson, in Proceeding of the 2003 International Geosci. Rem. Sens. 6, 4083 (2003).
  5. D. L. Donoho and I. M. Johnstone, Biometrica 81, 425 (1994).
  6. J. R. Sveinsson and J. A. Benediktsson, IEEE Trans. Geosci. Rem. Sens. 41, 2404 (2003).

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