Faster scaling algorithms for network problems
SIAM Journal on Computing
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Reconstructing convex polyominoes from horizontal and vertical projections
Theoretical Computer Science
An efficient implementation of a scaling minimum-cost flow algorithm
Journal of Algorithms
The discrete Radon transform and its approximate inversion via linear programming
Discrete Applied Mathematics
On the precise number of (0,1)-matrices in U(R,S)
Discrete Mathematics
On the computational complexity of reconstructing lattice sets from their x-rays
Discrete Mathematics
Approximating Binary Images from Discrete X-Rays
SIAM Journal on Optimization
An algorithm reconstructing convex lattice sets
Theoretical Computer Science
A Network Flow Algorithm for Reconstructing Binary Images from Continuous X-rays
Journal of Mathematical Imaging and Vision
Generic iterative subset algorithms for discrete tomography
Discrete Applied Mathematics
Solving Nonograms by combining relaxations
Pattern Recognition
A reasoning framework for solving nonograms
IWCIA'08 Proceedings of the 12th international conference on Combinatorial image analysis
A memetic approach to discrete tomography from noisy projections
Pattern Recognition
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We present a new algorithm for reconstructing binary images from their projections along a small number of directions. Our algorithm performs a sequence of related reconstructions, each using only two projections. The algorithm makes extensive use of network flow algorithms for solving the two-projection subproblems.Our experimental results demonstrate that the algorithm can compute highly accurate reconstructions from a small number of projections, even in the presence of noise. Although the effectiveness of the algorithm is based on certain smoothness assumptions about the image, even tiny, non-smooth details are reconstructed exactly. The class of images for which the algorithm is most effective includes images of convex objects, but images of objects that contain holes or consist of multiple components can also be reconstructed very well.