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Coefficient-Tracking Speckle Reducing Anisotropic Diffusion

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Image Analysis and Recognition (ICIAR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5627))

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Abstract

Speckle reducing anisotropic diffusion (SRAD) filter is introduced to significantly reduce speckle noise from images. Yet, SRAD suffers from the problems of ordinary diffusion filters, e.g., objects boundaries broadening and edges dislocation.This paper provides a more robust diffusion-filtering scheme, which is based on tracking the image main features across SRAD scale-space images. Coefficient-tracking SRAD (CSRAD) controls the amount of allowed diffusion based on the edges original location.CSRAD is tested on Berkley segmentation dataset. CSRAD results are subjectively compared with those of SRAD in terms of edge localization, smoothing enhancement, and features preserving. Experimental results show that CSRAD significantly reduced the features distortion and edges dislocation effects. Consequently, the entire diffusion process is enhanced.

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Author information

Authors and Affiliations

  1. Computer Science Department, The University of Western Ontario, London, ON, N6H5B7, Canada

    Walid Ibrahim & Mahmoud R. El-Sakka

Authors
  1. Walid Ibrahim
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  2. Mahmoud R. El-Sakka
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, Ontario, Canada

    Mohamed Kamel

  2. Faculty of Engineering, Institute of Biomedical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

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© 2009 Springer-Verlag Berlin Heidelberg

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Ibrahim, W., El-Sakka, M.R. (2009). Coefficient-Tracking Speckle Reducing Anisotropic Diffusion. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_14

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  • DOI: https://doi.org/10.1007/978-3-642-02611-9_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02610-2

  • Online ISBN: 978-3-642-02611-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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