TY - JOUR A1 - Osterloh, Kurt A1 - Bücherl, T. A1 - Zscherpel, Uwe A1 - Ewert, Uwe T1 - Image recovery by removing stochastic artefacts identified as local asymmetries T2 - Journal of Instrumentation N2 - Stochastic artefacts are frequently encountered in digital radiography and tomography with neutrons. Most obviously, they are caused by ubiquitous scattered radiation hitting the CCD-sensor. They appear as scattered dots and, at higher frequency of occurrence, they may obscure the image. Some of these dotted interferences vary with time, however, a large portion of them remains persistent so the problem cannot be resolved by collecting stacks of images and to merge them to a median image. The situation becomes even worse in computed tomography (CT) where each artefact causes a circular pattern in the reconstructed plane. Therefore, these stochastic artefacts have to be removed completely and automatically while leaving the original image content untouched. A simplified image acquisition and artefact removal tool was developed at BAM and is available to interested users. Furthermore, an algorithm complying with all the requirements mentioned above was developed that reliably removes artefacts that could even exceed the size of a single pixel without affecting other parts of the image. It consists of an iterative two-step algorithm adjusting pixel values within a 3 × 3 matrix inside of a 5 × 5 kernel and the centre pixel only within a 3 × 3 kernel, resp. It has been applied to thousands of images obtained from the NECTAR facility at the FRM II in Garching, Germany, without any need of a visual control. In essence, the procedure consists of identifying and tackling asymmetric intensity distributions locally with recording each treatment of a pixel. Searching for the local asymmetry with subsequent correction rather than replacing individually identified pixels constitutes the basic idea of the algorithm. The efficiency of the proposed algorithm is demonstrated with a severely spoiled example of neutron radiography and tomography as compared with median filtering, the most convenient alternative approach by visual check, histogram and power spectra analysis. PB - Inst. of Physics Publ. CY - London KW - Data processing methods KW - Image filtering KW - Pattern recognition KW - Cluster finding KW - Calibration and fitting methods PY - 2012 UR - https://opus4.kobv.de/opus4-bam/frontdoor/index/index/docId/25877 AN - OPUS4-25877 SN - 1748-0221 VL - 7 IS - April SP - 1 EP - 14 AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany