### Samenvatting

We propose an iterative approximate reconstruction method where we minimize the difference between reconstructions from subsets of multi scale measurements. To this end we interpret images not as scalar-valued functions but as sections through a fibered space. Information from previous reconstructions, which can be obtained at a coarser scale than the current one, is propagated by means of covariant derivatives on a vector bundle. The gauge field that is used to define the covariant derivatives is defined by the previously reconstructed image. An advantage of using covariant derivatives in the variational formulation of the reconstruction method is that with the number of iterations the accuracy of the approximation increases. The presented reconstruction method allows for a reconstruction at a resolution of choice, which can also be used to speed up the approximation at a finer level. An application of our method to reconstruction from a sparse set of differential features of a scale space representation of an image allows for a weighting of the features based on the sensitivity of those features to noise. To demonstrate the method we apply it to the reconstruction from singular points of a scale space representation of an image.

Originele taal-2 | Engels |
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Titel | Scale Space and Variational Methods in Computer Vision (Second International Conference, SSVM 2009, Voss, Norway, June 1-5, 2009, Proceedings) |

Redacteuren | X.-C. Tai, K. Morken, M. Lysaker, K.A. Lie |

Plaats van productie | Berlin |

Uitgeverij | Springer |

Pagina's | 377-388 |

ISBN van geprinte versie | 978-3-642-02255-5 |

DOI's | |

Status | Gepubliceerd - 2009 |

### Publicatie series

Naam | Lecture Notes in Computer Science |
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Volume | 5567 |

ISSN van geprinte versie | 0302-9743 |

## Vingerafdruk Duik in de onderzoeksthema's van 'Coarse-to-fine image reconstruction based on weighted differential features and background Gauge fields'. Samen vormen ze een unieke vingerafdruk.

## Citeer dit

Janssen, B. J., Duits, R., & Florack, L. M. J. (2009). Coarse-to-fine image reconstruction based on weighted differential features and background Gauge fields. In X-C. Tai, K. Morken, M. Lysaker, & K. A. Lie (editors),

*Scale Space and Variational Methods in Computer Vision (Second International Conference, SSVM 2009, Voss, Norway, June 1-5, 2009, Proceedings)*(blz. 377-388). (Lecture Notes in Computer Science; Vol. 5567). Springer. https://doi.org/10.1007/978-3-642-02256-2_32