Targeted Iterative Filtering

  • Freddie Åström
  • Michael Felsberg
  • George Baravdish
  • Claes Lundström
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7893)


The assessment of image denoising results depends on the respective application area, i.e. image compression, still-image acquisition, and medical images require entirely different behavior of the applied denoising method. In this paper we propose a novel, nonlinear diffusion scheme that is derived from a linear diffusion process in a value space determined by the application. We show that application-driven linear diffusion in the transformed space compares favorably with existing nonlinear diffusion techniques.


Mapping Function Regularization Term Initial Value Problem High Dynamic Range Multiplicative Noise 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Freddie Åström
    • 1
    • 2
  • Michael Felsberg
    • 1
    • 2
  • George Baravdish
    • 3
  • Claes Lundström
    • 2
    • 4
  1. 1.Computer Vision LaboratoryLinköping UniversitySweden
  2. 2.Center for Medical Image Science and VisualizationLinköping UniversitySweden
  3. 3.Department of Science and TechnologyLinköping UniversitySweden
  4. 4.Sectra ABSweden

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