Non-local adaptive structure tensors

  • Authors:

  • Vincent Doré;Reza Farrahi Moghaddam;Mohamed Cheriet

  • Affiliations:

  • Synchromedia Laboratory for Multimedia Communication in Telepresence, ícole de Technologie Supérieure, Montreal (Qc), Canada H3C 1K3 and Biomedical Imaging ICT, The Australian e-Health R ...;Synchromedia Laboratory for Multimedia Communication in Telepresence, ícole de Technologie Supérieure, Montreal (Qc), Canada H3C 1K3;Synchromedia Laboratory for Multimedia Communication in Telepresence, ícole de Technologie Supérieure, Montreal (Qc), Canada H3C 1K3

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2011

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Abstract

Structure tensors are used in several PDE-based methods to estimate information on the local structure in the image, such as edge orientation. They have become a common tool in many image processing applications. To integrate the local data information, the structure tensor is based on a local regularization of a tensorial product. In this paper, we propose a new regularization model based on the non-local properties of the tensor product. The resulting non-local structure tensor is effective in the restitution of the non homogeneity of the local orientation of the structures. It is particularly efficient in texture regions where patches repeat non locally. The new tensor regularization also offers the advantage of automatically adapting the smoothing parameter to the local structures of the tensor product. Finally, we explain how this new adaptive structure tensor can be plugged into two PDEs: an anisotropic diffusion and a shock filter. Comparisons with other tensor regularization methods and other PDEs demonstrate the clear advantage of using the non-local structure tensor.