Jointmotion estimation and layer segmentation in transparent image sequenc: application to noise reduction in X-ray image sequences

  • Authors:
  • Vincent Auvray;Patrick Bouthemy;Jean Liénard

  • Affiliations:
  • INRIA Centre Rennes-Bretagne-Atlantique, Rennes Cedex, France and General Electric Healthcare, Buc, France;INRIA Centre Rennes-Bretagne-Atlantique, Rennes Cedex, France;General Electric Healthcare, Buc, France

  • Venue:
  • EURASIP Journal on Advances in Signal Processing
  • Year:
  • 2009

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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 transparentmotion 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.