Title
Coarse-to-Fine Image Reconstruction Based on Weighted Differential Features and Background Gauge Fields
Abstract
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.
Year
DOI
Venue
2009
10.1007/978-3-642-02256-2_32
SSVM
Keywords
Field
DocType
approximation increase,weighted differential features,scale space representation,reconstructed image,fibered space,background gauge fields,covariant derivative,reconstruction method,iterative approximate reconstruction method,previous reconstruction,multi scale measurement,coarse-to-fine image,coarser scale,image reconstruction,value function,vector bundle,gauge field,scale space,singular point
Iterative reconstruction,Topology,Singular point of a curve,Covariant transformation,Vector bundle,Scale space,Algorithm,Gauge theory,Covariant derivative,Gauge (firearms),Mathematics
Conference
Volume
ISSN
Citations 
5567
0302-9743
4
PageRank 
References 
Authors
0.42
12
3
Name
Order
Citations
PageRank
Bart Janssen1242.56
Remco Duits238033.83
L. M. J. Florack31212210.47