Title of article :
A Linear Image Reconstruction Framework Based on Sobolev
Type Inner Products
Author/Authors :
Bart Janssen، نويسنده , , FRANS KANTERS?، نويسنده , , REMCO DUITS?، نويسنده , , LUC FLORACK، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2006
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 L2-error
than the reconstructions obtained by previously proposed linear methods.
Keywords :
Scale space , reconstruction , sampling , deep structure
Journal title :
INTERNATIONAL JOURNAL OF COMPUTER VISION
Journal title :
INTERNATIONAL JOURNAL OF COMPUTER VISION