Bayesian non local means-based speckle filtering

Author

Coupe, Pierrick ; Hellier, Pierre ; Kervrann, Charles ; Barillot, Christian

Author_Institution

CNRS UMR 6074, Univ. of Rennes I, Rennes

fYear

2008

fDate

14-17 May 2008

Firstpage

1291

Lastpage

1294

Abstract

In ultrasound (US) imaging, denoising is intended to improve quantitative image analysis techniques. In this paper, a new version of the non local (nl) means filter adapted for US images is proposed. Originally developed for Gaussian noise removal, a Bayesian framework is used to adapt the NL means filter for speckle noise. Experiments were carried out on synthetic data sets with different speckle simulations. Results show that our NL means-based speckle filter outperforms the classical implementation of the NL means filter, as well as two other speckle adapted denoising methods (SRAD and SBF filters).

Keywords

Bayes methods; Gaussian noise; biomedical ultrasonics; image denoising; image enhancement; image restoration; medical image processing; speckle; Bayesian non local means filtering; SBF filters; SRAD filters; speckle adapted denoising methods; speckle filtering; speckle noise; ultrasound imaging; Acoustic applications; Acoustic imaging; Adaptive filters; Bayesian methods; Gaussian noise; Image analysis; Image restoration; Noise reduction; Speckle; Ultrasonic imaging; Acoustic applications; Acoustics; Image enhancement; Image restoration;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on

Conference_Location

Paris

Print_ISBN

978-1-4244-2002-5

Electronic_ISBN

978-1-4244-2003-2

Type

conf

DOI

10.1109/ISBI.2008.4541240

Filename

4541240