Boundary Ghosts for Discrete Tomography
| Autor: | Timothy Petersen, Matthew Ceko, Robert Tijdeman, Imants D. Svalbe |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Pixel Computer science Applied Mathematics Mathematical analysis String (computer science) Binary number Boundary (topology) 02 engineering and technology Iterative reconstruction Condensed Matter Physics Mojette Transform High Energy Physics::Theory Projection (mathematics) Computer Science::Computer Vision and Pattern Recognition Modeling and Simulation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Geometry and Topology Computer Vision and Pattern Recognition Discrete tomography |
| Zdroj: | Journal of Mathematical Imaging and Vision. 63:428-440 |
| ISSN: | 1573-7683 0924-9907 |
| DOI: | 10.1007/s10851-020-01010-2 |
| Popis: | Discrete tomography reconstructs an image of an object on a grid from its discrete projections along relatively few directions. When the resulting system of linear equations is under-determined, the reconstructed image is not unique. Ghosts are arrays of signed pixels that have zero sum projections along these directions; they define the image pixel locations that have non-unique solutions. In general, the discrete projection directions are chosen to define a ghost that has minimal impact on the reconstructed image. Here we construct binary boundary ghosts, which only affect a thin string of pixels distant from the object centre. This means that a large portion of the object around its centre can be uniquely reconstructed. We construct these boundary ghosts from maximal primitive ghosts, configurations of $$2^N$$ connected binary ( $$\pm 1$$ ) points over N directions. Maximal ghosts obfuscate image reconstruction and find application in secure storage of digital data. |
| Databáze: | OpenAIRE |
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