Journal of Applied Crystallography · 2008 · 1.2K citations · 17 references
ComputingComputer ScienceBiomedical ImagingDigital ImagingMachine VisionFourier OpticsImage AnalysisTexture AnalysisData InversionDetectorsDiscretizationInversionsMinimizationPoisson Process EstimationPoisson Process ModelsPole Figures
The paper introduces a novel algorithm for estimating orientation density functions from diffraction pole figures, particularly effective for sharp textures and high‑resolution data measured with arbitrarily scattered specimen directions. The algorithm solves a minimization problem modeling diffraction counts as a Poisson process, employing radially symmetric discretization and fast Fourier techniques to achieve smooth, high‑performance ODF estimation. A free implementation of the algorithm is available within the MTEX texture analysis software.
A novel algorithm for ODF (orientation density function) estimation from diffraction pole figures is presented which is especially well suited for sharp textures and high-resolution pole figures measured with respect to arbitrarily scattered specimen directions, e.g. by area detectors. The estimated ODF is computed as the solution of a minimization problem which is based on a model of the diffraction counts as a Poisson process. The algorithm applies discretization by radially symmetric functions and fast Fourier techniques to guarantee smooth approximation and high performance. An implementation of the algorithm is freely available as part of the texture analysis software MTEX .
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