Linear Image Reconstruction from Scale Space Interest Points
Bart J. Janssen, Technische Universiteit Eindhoven, Eindhoven, The Netherlands
Exploration of information content of features that are present in the scale space of an image has led to the development of reconstruction algorithms. These algorithms aim for a reconstruction from the features that is visually close to the image from which the features are extracted. We propose a linear reconstruction framework that generalizes a previously proposed scheme. As an example we propose a prior that is a norm formed by a Sobolev type inner product. We apply the reconstruction algorithm to the reconstruction from non-Morse critical points of a scale space image. Scale is taken as a control parameter. These type of points are also referred to in the literature as degenerate spatial critical points or as toppoints or catastrophes.
Bart J. Janssen, Technische Universiteit Eindhoven, Eindhoven, The Netherlands
Seminar • 01 July 2005
AbstractExploration of information content of features that are present in the scale space of an image has led to the development of reconstruction algorithms. These algorithms aim for a reconstruction from the features that is visually close to the image from which the features are extracted. We propose a linear reconstruction framework that generalizes a previously proposed scheme. As an example we propose a prior that is a norm formed by a Sobolev type inner product. We apply the reconstruction algorithm to the reconstruction from non-Morse critical points of a scale space image. Scale is taken as a control parameter. These type of points are also referred to in the literature as degenerate spatial critical points or as toppoints or catastrophes.