Three-Dimensional Statistical Data Security Problems
SIAM Journal on Computing
The discrete Radon transform and its approximate inversion via linear programming
Discrete Applied Mathematics
On the computational complexity of reconstructing lattice sets from their x-rays
Discrete Mathematics
On the comptational complexity of determining polyatomic structures by X-rays
Theoretical Computer Science
Stability and instability in discrete tomography
Digital and image geometry
Stability in discrete tomography: some positive results
Discrete Applied Mathematics - Special issue: Advances in discrete geometry and topology (DGCI 2003)
On Stability, Error Correction, and Noise Compensation in Discrete Tomography
SIAM Journal on Discrete Mathematics
Some Properties of Image-Processing Operations on Projection Sets Obtained from Digital Pictures
IEEE Transactions on Computers
Characterization of Binary Patterns and Their Projections
IEEE Transactions on Computers
On the stability of reconstructing lattice sets from x-rays along two directions
DGCI'05 Proceedings of the 12th international conference on Discrete Geometry for Computer Imagery
Decision Trees in Binary Tomography for Supporting the Reconstruction of hv-Convex Connected Images
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Bounds on the difference between reconstructions in binary tomography
DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery
A method for feature detection in binary tomography
DGCI'13 Proceedings of the 17th IAPR international conference on Discrete Geometry for Computer Imagery
Discrete tomography for inscribable lattice sets
Discrete Applied Mathematics
Bounds on the quality of reconstructed images in binary tomography
Discrete Applied Mathematics
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In the present paper we mathematically prove several stability results concerning the problem of reconstructing binary pictures from their noisy projections taken from two directions. Stability is a major requirement in practice, because projections are often affected by noise due to the nature of measurements. Reconstruction from projections taken along more than two directions is known to be a highly unstable task. Contrasting this result we prove several theorems showing that reconstructions from two directions closely resemble the original picture when the noise level is low and the original picture is uniquely determined by its projections.