Abstract

This paper presents a semidiscrete alternative to the theory of neurogeometry of vision, due to Citti, Petitot, and Sarti. We propose a new ingredient, namely, working on the group of translations and discrete rotations $SE(2,N)$. The theoretical side of our study relates the stochastic nature of the problem with the Moore group structure of $SE(2,N)$. Harmonic analysis over this group leads to very simple finite dimensional reductions. We then apply these ideas to the inpainting problem which is reduced to the integration of a completely parallelizable finite set of Mathieu-type diffusions (indexed by the dual of $SE(2,N)$ in place of the points of the Fourier plane, which is a drastic reduction). The integration of the the Mathieu equations can be performed by standard numerical methods for elliptic diffusions and leads to a very simple and efficient class of inpainting algorithms. We illustrate the performances of the method on a series of deeply corrupted images.

Keywords

  1. sub-Riemannian geometry
  2. neurogeometry
  3. hypoelliptic diffusion
  4. generalized Fourier transform

MSC codes

  1. Primary
  2. 94A08; Secondary
  3. 35H10
  4. 53C17

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Information & Authors

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Published In

cover image SIAM Journal on Imaging Sciences
SIAM Journal on Imaging Sciences
Pages: 669 - 695
ISSN (online): 1936-4954

History

Submitted: 12 June 2013
Accepted: 17 January 2014
Published online: 24 April 2014

Keywords

  1. sub-Riemannian geometry
  2. neurogeometry
  3. hypoelliptic diffusion
  4. generalized Fourier transform

MSC codes

  1. Primary
  2. 94A08; Secondary
  3. 35H10
  4. 53C17

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