Publication
Title
A semi-automatic algorithm for grey level estimation in tomography
Author
Abstract
Discrete tomography focuses on the reconstruction of images that contain only a few grey levels from their projections. By incorporating prior knowledge about the set of grey levels, the required number of projections can be reduced substantially. In practical applications, however, the number of grey levels is often known in advance, yet the actual grey level values are unknown. Moreover, it can be difficult to estimate these grey levels, particularly if only a small number of projections are available. In this paper, we propose a semi-automatic approach for grey level estimation that can be used as a preprocessing step before applying discrete tomography algorithms. After an initial, non-discrete reconstruction has been computed, the user first selects some regions that are likely to correspond with the respective grey levels. The fact that these regions should be constant in the original image is then used as prior knowledge in the grey level estimation algorithm. We present the results of a series of simulation experiments, demonstrating the accuracy and robustness of our approach.
Language
English
Source (journal)
Pattern recognition letters. - Amsterdam
Publication
Amsterdam : 2011
ISSN
0167-8655
DOI
10.1016/J.PATREC.2010.09.001
Volume/pages
32 :9 (2011) , p. 1395-1405
ISI
000291771100018
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 09.02.2011
Last edited 15.11.2022
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