Name
Abstract | ||
|---|---|---|
Generating 2D noise with local, space-varying spectral characteristics is vital where random noise fields with spatially heterogeneous statistical properties are observed and need to be simulated. A realistic, non-stationary noise generator relying on experimental data is presented. That generator is desired in areas such as photography and radiography. For example, before performing actual X-ray imaging in practice, output images are simulated to assess and improve setups. For that purpose, realistic film noise modelling is crucial because noise downgrades the detectability of visual signals. The presented film noise synthesiser improves the realism and value of radiographic simulations significantly, allowing more realistic assessments of radiographic test setups. The method respects space-varying spectral characteristics and probability distributions, locally simulating noise with realistic granularity and contrast. The benefits of this approach are to respect the correlation between noise and image as well as internal correlation, the fast generation of any number of unique noise samples, the exploitation of real experimental data, and its statistical non-stationarity. The combination of these benefits is not available in existing work. Validation of the new technique was undertaken in the field of industrial radiography. While applied to that field here, the technique is general and can also be utilised in any other field where the generation of 2D noise with local, space-varying statistical properties is necessary. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TIP.2019.2955284 | IEEE TRANSACTIONS ON IMAGE PROCESSING |
Keywords | DocType | Volume |
Correlation, Radiography, Computational modeling, Silver, Optical films, Optical imaging, Two dimensional displays, Image quality, noise simulation, nondestructive testing, radiography | Journal | 29 |
Issue | ISSN | Citations |
1 | 1057-7149 | 1 |
PageRank | References | Authors |
0.35 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sebastian Eckel | 1 | 1 | 0.35 |
| Peter Huthwaite | 2 | 1 | 0.35 |
| Uwe Zscherpel | 3 | 28 | 3.66 |
| Andreas Schumm | 4 | 1 | 0.35 |
| Nicolas Paul | 5 | 1 | 0.35 |