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A Linear Image Reconstruction Framework Based on Sobolev Type Inner Products

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Abstract

Exploration of information content of features that are present in images has led to the development of several reconstruction algorithms. These algorithms aim for a reconstruction from the features that is visually close to the image from which the features are extracted. Degrees of freedom that are not fixed by the constraints are disambiguated with the help of a so-called prior (i.e. a user defined model). We propose a linear reconstruction framework that generalizes a previously proposed scheme. The algorithm greatly reduces the complexity of the reconstruction process compared to non-linear methods. As an example we propose a specific prior and apply it to the reconstruction from singular points. The reconstruction is visually more attractive and has a smaller 핃2-error than the reconstructions obtained by previously proposed linear methods.

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Authors and Affiliations

  1. Eindhoven University of Technology, Den Dolech 2, Postbus 513, 5600 MB, Eindhoven, The Netherlands

    Bart Janssen, Frans Kanters, Remco Duits, Luc Florack & Bart ter Haar Romeny

Authors
  1. Bart Janssen
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  2. Frans Kanters
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  3. Remco Duits
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  4. Luc Florack
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  5. Bart ter Haar Romeny
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Corresponding author

Correspondence to Bart Janssen.

Additional information

Bart Jansen, Frans Kanters and Remco Duits are joint main authors of this article.

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Janssen, B., Kanters, F., Duits, R. et al. A Linear Image Reconstruction Framework Based on Sobolev Type Inner Products. Int J Comput Vision 70, 231–240 (2006). https://doi.org/10.1007/s11263-006-6703-9

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  • DOI: https://doi.org/10.1007/s11263-006-6703-9

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