Nonlocal means-based speckle filtering for ultrasound images

Authors:
Pierrick Coupé;Pierre Hellier;Charles Kervrann;Christian Barillot
Affiliations:
CNRS UMR 6074, IRISA, University of Rennes I and INRIA and INSERM, Rennes, France;CNRS UMR 6074, IRISA, University of Rennes I and INRIA and INSERM, Rennes, France;INRIA, IRISA, Rennes and INRA, UR341 Mathématiques et Informatique Appliquées, Jouy en Josas, France;CNRS UMR 6074, IRISA, University of Rennes I and INRIA and INSERM, Rennes, France
Venue:
IEEE Transactions on Image Processing
Year:
2009

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Abstract

In image processing, restoration is expected to improve the qualitative inspection of the image and the performance of quantitative image analysis techniques. In this paper, an adaptation of the nonlocal (NL)-means filter is proposed for speckle reduction in ultrasound (US) images. Originally developed for additive white Gaussian noise, we propose to use a Bayesian framework to derive a NL-means filter adapted to a relevant ultrasound noise model. Quantitative results on synthetic data show the performances of the proposed method compared to well-established and state-of-the-art methods. Results on real images demonstrate that the proposed method is able to preserve accurately edges and structural details of the image.