BayesShrink Ridgelets for Image Denoising

  • Nezamoddin Nezamoddini-Kachouie
  • Paul Fieguth
  • Edward Jernigan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3211)


The wavelet transform has been employed as an efficient method in image denoising via wavelet thresholding and shrinkage. The ridgelet transform was recently introduced as an alternative to the wavelet representation of two dimensional signals and image data. In this paper, a BayesShrink ridgelet denoising technique is proposed and its denoising performance is compared with a previous VisuShrink ridgelet method. To derive the results, different wavelet bases such as Daubechies, symlets and biorthogonal are used. Experimental results show that BayesShrink ridgelet denoising yields superior image quality and higher SNR than VisuShrink.


Wavelet Coefficient Wavelet Base Image Denoising Denoising Method Wavelet Shrinkage 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Nezamoddin Nezamoddini-Kachouie
    • 1
  • Paul Fieguth
    • 1
  • Edward Jernigan
    • 1
  1. 1.Department of Systems Design EngineeringUniversity of WaterlooWaterlooCanada

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