Density Driven Diffusion

  • Freddie Åström
  • Vasileios Zografos
  • Michael Felsberg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7944)


In this work we derive a novel density driven diffusion scheme for image enhancement. Our approach, called D3, is a semi-local method that uses an initial structure-preserving oversegmentation step of the input image. Because of this, each segment will approximately conform to a homogeneous region in the image, allowing us to easily estimate parameters of the underlying stochastic process thus achieving adaptive non-linear filtering. Our method is capable of producing competitive results when compared to state-of-the-art methods such as non-local means, BM3D and tensor driven diffusion on both color and grayscale images.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Freddie Åström
    • 1
    • 2
  • Vasileios Zografos
    • 1
  • Michael Felsberg
    • 1
    • 2
  1. 1.Computer Vision LaboratoryLinköping UniversitySweden
  2. 2.Center for Medical Image Science and Visualization (CMIV)Linköping UniversitySweden

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