Grayscale Uncertainty of Projection Geometries and Projections Sets
| Autor: | Péter Balázs, Gábor Lékó, László Varga |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Pixel
010401 analytical chemistry 02 engineering and technology 01 natural sciences Grayscale Measure (mathematics) 0104 chemical sciences Hyperplane Linear algebra 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Tomography Projection (set theory) Algorithm Linear equation Mathematics |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030510015 IWCIA |
| Popis: | In some cases of tomography, the projection acquisition process has limits, and thus one cannot gain enough projections for an exact reconstruction. In this case, the low number of projections leads to a lack of information, and uncertainty in the reconstructions. In practice this means that the pixel values of the reconstruction are not uniquely determined by the measured data and thus can have variable values. In this paper, we provide a theoretically proven uncertainty measure that can be used for measuring the variability of pixel values in grayscale reconstructions. The uncertainty values are based on linear algebra and measure the slopes of the hyperplane of solutions in the algebraic formulation of tomography. The methods can also be applied for any linear equation system, that satisfy a given set of conditions. Using the uncertainty measure, we also derive upper and lower limits on the possible pixel values in tomographic reconstructions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|