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Noise Level Estimation for Image Processing

  • Gwanggil Jeon
  • SeokHoon Kang
  • Young-Sup Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7425)

Abstract

This paper compares the results between two well known noise level estimation algorithms. We address the issue of estimating the variance of additive white Gaussian noise in digital images, even with large textured areas. Noise can significantly influence the quality of digital images. This method is based on two approaches. Both algorithms were introduced and we tested both algorithms with 5 artificial images and 8 natural images. One approach searches intensity-homogeneous blocks and then we estimate the noise variance in these blocks. The other method is based on wavelet transform, we obtain variance of additive white Gaussian noise using coefficients of wavelet transform. Based on the results, we adaptively choose the method and obtain the most appropriate noise level.

Keywords

variance noise homogeneous area wavelet 

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References

  1. 1.
    Brailean, J., Kleihorst, R., Efstratiadis, S., Katsaggelos, A., Lagendijk, R.: Noise reduction filter for dynamic image sequences: A review. Proceedings of the IEEE 83(9), 1272–1292 (1995)CrossRefGoogle Scholar
  2. 2.
    Battiato, S., Bosco, A., Mancuso, M., Spampinato, G.: Adaptive temporal filtering for CFA video sequences. In: Proceedings of IEEE ACIVS 2002 Advanced Concepts for Intelligent Vision Systems 2002, pp. 19–24. Ghent University, Belgium (2002)Google Scholar
  3. 3.
    Bosco, A., Findlater, K., Battiato, S., Castorina, A.: A noise reduction filter for full-frame imaging devices. IEEE Transactions on Consumer Electronics 49(3), 676–682 (2003)CrossRefGoogle Scholar
  4. 4.
    Bosco, A., Findlater, K., Battiato, S., Castorina, A.: A temporal noise reduction filter based on full-frame data image sensors. In: Proceedings ICCE 2003, Los Angeles (June 2003)Google Scholar
  5. 5.
    Amer, A., Dubois, E.: Fast and reliable structure-oriented video noise estimation. IEEE Transactions on Circuits and Systems for Video Technology 15(1), 840–843 (2002)Google Scholar
  6. 6.
    Olsen, S.I.: Noise variance estimation in images. In: Proceedings of the 8th Scandinavian Conference on Image Analysis, Troms, Norway (1993)Google Scholar
  7. 7.
    Donoho, D.L., Johnstone, I.M.: Ideal spatial adaptation via wavelet shrinkage. Biometrika 81, 425–455 (1994)MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Gwanggil Jeon
    • 1
  • SeokHoon Kang
    • 1
  • Young-Sup Lee
    • 1
  1. 1.Department of Embedded Systems EngineeringUniversity of IncheonIncheonKorea

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