Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Nonlinear Diffusion Filters without Parameters for Image Segmentation
Year:2009
Research Areas
  • Mathematics,
  • Automatic
Information
Abstract
Nonlinear diffusion filtering seeks to improve images qualitatively by removing noise while preserving details and even enhancing edges. However, well known implementations are sensitive to parameters which are necessarily tuned to sharpen a narrow range of edge slopes. In this work, we have selected a nonlinear diffusion filter without control parameters. It has been guided searching the optimum balance between time performance and resulting quality suitable for automatic segmentation tasks. Using a semi-implicit numerical scheme, we have determined the relationship between the slope range to sharpen and the diffusion time. It has also been selected the diffusivity with optimum performances. Several diffusion filters have been applied to noisy computed tomography images and evaluated for their suitability to the medical image segmentation. Experimental results show that our proposal of filter performs quite well in relation to others.
International
Si
Congress
Computer Analysis of Images and Patterns, 13th International Conference, CAIP 2009
960
Place
Münster, Germany
Reviewers
Si
ISBN/ISSN
978-3-642-03766-5
10.1007/978-3-642-03767-2_63
Start Date
02/09/2009
End Date
04/09/2009
From page
517
To page
524
Computer Analysis of Images and Patterns, 13th International Conference, LNCS, Volume 5702/2009
Participants
  • Autor: Carlos Platero Dueñas (UPM)
  • Autor: Fco. Javier Sanguino Botella (UPM)
  • Autor: Olga Velasco Manuel (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Bioingeniería Aplicada
  • Departamento: Electrónica, Automática e Informática Industrial
  • Departamento: Matemática Aplicada (E.U.I.T. Industrial)
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