Dynamic angle selection in binary tomography

Authors:
K. Joost Batenburg;Willem Jan Palenstijn;PéTer BaláZs;Jan Sijbers
Affiliations:
Centrum Wiskunde & Informatica, Science Park 123, NL-1098 XG Amsterdam, The Netherlands and Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk, Belgium;Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk, Belgium;Department of Image Processing and Computer Graphics, University of Szeged, Árpád tér 2, H-6720 Szeged, Hungary;Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk, Belgium
Venue:
Computer Vision and Image Understanding
Year:
2013

Citing 11
Cited 0

On the computational complexity of reconstructing lattice sets from their x-rays

Discrete Mathematics
Principles of computerized tomographic imaging

Principles of computerized tomographic imaging
Advances in Discrete Tomography and Its Applications (Applied and Numerical Harmonic Analysis)

Advances in Discrete Tomography and Its Applications (Applied and Numerical Harmonic Analysis)
Fundamentals of Computerized Tomography: Image Reconstruction from Projections

Fundamentals of Computerized Tomography: Image Reconstruction from Projections
Discrete tomography by convex-concave regularization and D.C. programming

Discrete Applied Mathematics - Special issue: IWCIA 2003 - Ninth international workshop on combinatorial image analysis
Bounds on the difference between reconstructions in binary tomography

DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery
Direction-dependency of binary tomographic reconstruction algorithms

Graphical Models
Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

IEEE Transactions on Information Theory
Compressed sensing

IEEE Transactions on Information Theory
DART: A Practical Reconstruction Algorithm for Discrete Tomography

IEEE Transactions on Image Processing
Projection selection dependency in binary tomography

Acta Cybernetica

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present an algorithm for the dynamic selection of projection angles in binary tomography. Based on the information present in projections that have already been measured, a new projection angle is computed, which aims to maximize the information gained by adding this projection to the set of measurements. The optimization model used for angle selection is based on a characterization of solutions of the binary reconstruction problem, and a related definition of information gain. From this formal model, an algorithm is obtained by several approximation steps. Results from a series of simulation experiments demonstrate that the proposed angle selection scheme is indeed capable of finding angles for which the reconstructed image is much more accurate than for the standard angle selection scheme.