Morphological signal processing and the slope transform
Signal Processing - Special issue on mathematical morphology and its applications to signal processing
A course in computational algebraic number theory
A course in computational algebraic number theory
The discrete Radon transform and its approximate inversion via linear programming
Discrete Applied Mathematics
Principles of computerized tomographic imaging
Principles of computerized tomographic imaging
Reconstruction of lattice sets from their horizontal, vertical and diagonal X-rays
Discrete Mathematics
On the algorithmic inversion of the discrete Radon transform
Theoretical Computer Science
Sampling properties of the discrete radon transform
Discrete Applied Mathematics - The 2001 international workshop on combinatorial image analysis (IWCIA 2001)
On Stability, Error Correction, and Noise Compensation in Discrete Tomography
SIAM Journal on Discrete Mathematics
Using graphs for some discrete tomography problems
Discrete Applied Mathematics
An evolutionary algorithm for discrete tomography
Discrete Applied Mathematics - Special issue: IWCIA 2003 - Ninth international workshop on combinatorial image analysis
A benchmark evaluation of large-scale optimization approaches to binary tomography
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
The mojette transform: the first ten years
DGCI'05 Proceedings of the 12th international conference on Discrete Geometry for Computer Imagery
Bounds on the difference between reconstructions in binary tomography
DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery
Bounds on the quality of reconstructed images in binary tomography
Discrete Applied Mathematics
Approximate Discrete Reconstruction Algorithm
Fundamenta Informaticae - Strategies for Tomography
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Discrete tomography deals with image reconstruction of an object with finitely many gray levels (such as two). Different approaches are used to model the raw detector reading. The most popular models are line projection with a lattice of points and strip projection with a lattice of pixels/cells. The line-based projection model fits some applications but involves a major approximation since the x-ray beams of finite widths are simplified as line integrals. The strip-based projection model formulates projection equations according to the fractional areas of the intersection of each strip-shaped beam and the rectangular grid of an image to be reconstructed, so is more realistic in some applications. In this paper, we characterize the strip-based projection model and establish an equivalence between the system matrices generated by the strip-based and line-based projection models.