Title
Singular Value Decomposition For The Truncated Hubert Transform
Abstract
Starting from a breakthrough result by Gelfand and Graev, inversion of the Hilbert transform became a very important tool for image reconstruction in tomography. In particular, their result is useful when the tomographic data are truncated and one deals with an interior problem. As was established recently, the interior problem admits a stable and unique solution when some a priori information about the object being scanned is available. The most common approach to solving the interior problem is based on converting it to the Hilbert transform and performing analytic continuation. Depending on what type of tomographic data are available, one gets different Hilbert inversion problems. In this paper, we consider two such problems and establish singular value decomposition for the operators involved. We also propose algorithms for performing analytic continuation. © 2010 IOP Publishing Ltd.
Publication Date
11-9-2010
Publication Title
Inverse Problems
Volume
26
Issue
11
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1088/0266-5611/26/11/115011
Copyright Status
Unknown
Socpus ID
78049442470 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/78049442470
STARS Citation
Katsevich, A., "Singular Value Decomposition For The Truncated Hubert Transform" (2010). Scopus Export 2010-2014. 10.
https://stars.library.ucf.edu/scopus2010/10