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BIAS AND NOISE REMOVAL FROM MAGNITUDE MR IMAGES

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Computer Vision and Graphics

Part of the book series: Computational Imaging and Vision ((CIVI,volume 32))

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Abstract

This paper presents a novel method of bias removing from the Rice distributed data. This method is based on developing the inverse formula applied to the function determining the expected value of the Rice distribution. Two algorithms for magnitude image denoising in a wavelet domain are developed. These algorithms use the proposed method of bias removal for the scaling coefficients correction. The denoising performance is better in comparison with the method based on processing the squared magnitude images.

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REFERENCES

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Author information

Authors and Affiliations

  1. Institute of Radioelectronics, Warsaw University of Technology, Poland

    Marian Kazubek

Authors
  1. Marian Kazubek
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Editor information

Editors and Affiliations

  1. Silesian University of Technology, Gliwice, Poland

    K. Wojciechowski

  2. Silesian University of Technology, Gliwice, Poland

    B. Smolka

  3. Silesian University of Technology, Gliwice, Poland

    H. Palus

  4. The University of Western Australia, Crawley, Australia

    R.S. Kozera

  5. Warsaw University of Technology, Warsaw, Poland

    W. Skarbek

  6. The University of Western Australia, Crawley, Australia

    L. Noakes

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© 2006 Springer

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Kazubek, M. (2006). BIAS AND NOISE REMOVAL FROM MAGNITUDE MR IMAGES. In: Wojciechowski, K., Smolka, B., Palus, H., Kozera, R., Skarbek, W., Noakes, L. (eds) Computer Vision and Graphics. Computational Imaging and Vision, vol 32. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4179-9_136

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  • DOI: https://doi.org/10.1007/1-4020-4179-9_136

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-4178-5

  • Online ISBN: 978-1-4020-4179-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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