Ultrasound image denoising via maximum a posteriori estimation of wavelet coefficients

A. Achim, A. Bezerianos, P. Tsakalides

Research output: Contribution to journalConference articlepeer-review

17 Scopus citations


Speckle noise removal by means of digital image processors could improve the diagnostic potential of medical ultrasound. This paper addresses the speckle suppression issue within the framework of wavelet analysis. As a first step of our approach, the logarithm of the original image is decomposed into several scales through a multiresolution analysis employing the 2-D wavelet transform. Then, we design a maximum a posteriori (MAP) estimator, which relies on a recently introduced statistical representation for the wavelet coefficients of ultrasound images [1]. We use an alpha-stable model to develop a blind noise-removal processor that performs a non-linear operation on the data. Finally, we compare our technique to current state-of-the-art denoising method applied on actual ultrasound images and we find it more effective, both in terms of speckle reduction and signal detail preservation.

Original languageEnglish (US)
Pages (from-to)2553-2556
Number of pages4
JournalAnnual Reports of the Research Reactor Institute, Kyoto University
StatePublished - Dec 1 2001
Event23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Istanbul, Turkey
Duration: Oct 25 2001Oct 28 2001


  • Alpha-stable distributions
  • MAP estimation
  • Speckle noise
  • Wavelet transform

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Mechanical Engineering


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