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  • Research Article
  • Open Access

Joint Motion Estimation and Layer Segmentation in Transparent Image Sequences—Application to Noise Reduction in X-Ray Image Sequences

EURASIP Journal on Advances in Signal Processing20092009:647262

https://doi.org/10.1155/2009/647262

  • Received: 27 November 2008
  • Accepted: 6 April 2009
  • Published:

Abstract

This paper is concerned with the estimation of the motions and the segmentation of the spatial supports of the different layers involved in transparent X-ray image sequences. Classical motion estimation methods fail on sequences involving transparent effects since they do not explicitly model this phenomenon. We propose a method that comprises three main steps: initial block-matching for two-layer transparent motion estimation, motion clustering with 3D Hough transform, and joint transparent layer segmentation and parametric motion estimation. It is validated on synthetic and real clinical X-ray image sequences. Secondly, we derive an original transparent motion compensation method compatible with any spatiotemporal filtering technique. A direct transparent motion compensation method is proposed. To overcome its limitations, a novel hybrid filter is introduced which locally selects which type of motion compensation is to be carried out for optimal denoising. Convincing experiments on synthetic and real clinical images are also reported.

Keywords

  • Image Sequence
  • Noise Reduction
  • Motion Estimation
  • Parametric Motion
  • Joint Motion

Publisher note

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Authors’ Affiliations

(1)
INRIA Centre Rennes-Bretagne-Atlantique, Campus universitaire de Beaulieu, 35042 Rennes Cedex, France
(2)
General Electric Healthcare, 283 rue de la Miniere, 78530 Buc, France

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