TY - JOUR A1 - Eckel, S. A1 - Zscherpel, Uwe A1 - Huthwaite, P. A1 - Paul, N. A1 - Schumm, A. T1 - Radiographic film system classification and noise characterisation by a camera-based digitisation procedure N2 - Extracting statistical characteristics from radiographic films is vital for film system classification and contrast sensitivity evaluation and serves as a basis for film noise simulation. A new method for digitising radiographic films in order to extract these characteristics is presented. The method consists of a camera-based setup and image processing procedure to digitise films. Correct optical density values and granularity can be extracted from the digitised images, which are equal to results obtained by standardised measurement procedures. Specific statistical characteristics of film noise are theoretically derived and subsequently verified by the obtained data, including characteristics such as Gaussianity and spatial spectral characteristics of the optical density fluctuations. It is shown that the presented method correctly measures the granularity of film noise and can therefore replace time-consuming microdensitometer measurements traditionally required for film system classifications. Additionally, the inherent unsharpness of film systems was investigated and compared with literature data. This comparison serves as another validation approach of the presented method. KW - Radiography KW - Image processing KW - Film noise KW - Film system classification KW - Digitisation PY - 2020 DO - https://doi.org/10.1016/j.ndteint.2020.102241 SN - 0963-8695 VL - 111 IS - 4 SP - 102241 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-50517 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Eckel, S. A1 - Huthwaite, P. A1 - Zscherpel, Uwe A1 - Schumm, A. A1 - Paul, N. T1 - Realistic film noise generation based on experimental noise spectra N2 - 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. KW - Nondestructive testing KW - Image quality KW - Noise simulation KW - Radiography PY - 2020 DO - https://doi.org/10.1109/TIP.2019.2955284 SN - 1057-7149 VL - 29 SP - 2987 EP - 2998 PB - IEEE Xplore CY - Washington, D.C. AN - OPUS4-50518 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ulbricht, Alexander A1 - Gollwitzer, Christian A1 - Kupsch, Andreas A1 - Léonard, Fabien A1 - Müller, Bernd R. A1 - Oesch, Tyler A1 - Onel, Yener A1 - Thiede, Tobias A1 - Zscherpel, Uwe ED - Puente León, F. ED - Zagar, B. T1 - Moderne Methoden der CT-gestützten Strukturanalyse T1 - Modern techniques of CT based structure analysis N2 - Durch den großflächigen Einsatz der Computertomographie (CT) in unterschiedlichen Industriebereichen steigen auch die Anforderungen an die quantitative Bildanalyse. Subjektive Bildwahrnehmung muss durch objektive Algorithmen ersetzt werden. In diesem Artikel stellt die Bundesanstalt für Materialforschung und -prüfung (BAM), die seit den 1980er Jahren an der Entwicklung der industriellen CT beteiligt ist, anhand ausgewählter Beispiele den aktuellen Stand ihrer Analysemethoden an verschiedenen Anwendungsbeispielen der CT vor. N2 - The increasing use of computed tomography (CT) in various industrial sectors requires more sophisticated techniques of quantitative image analysis. Subjective image perception needs to be replaced by objective algorithms. The German Federal Institute for Materials Research and Testing (BAM) has been involved in the development of industrial CT since the 1980s. This paper summarizes the current status of quantitative 3D image analysis techniques based on selected examples. KW - Computed tomography KW - Computertomographie KW - Röntgen-Refraktion KW - X-Ray refraction KW - Schadensanalyse KW - Damage analysis KW - Normung KW - standardization PY - 2020 DO - https://doi.org/10.1515/teme-2019-0125 SN - 0171-8096 SN - 2196-7113 VL - 87 IS - 2 SP - 81 EP - 91 PB - de Gruyter CY - Berlin AN - OPUS4-50337 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -