A greedy method for reconstructing polycrystals from three-dimensional X-ray diffraction data
Author(s) -
Arun K. Kulshreshth,
Andreas Alpers,
Gábor T. Herman,
Erik Knudsen,
Lajos Rodek,
Henning Friis Poulsen
Publication year - 2009
Publication title -
inverse problems and imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.755
H-Index - 40
eISSN - 1930-8345
pISSN - 1930-8337
DOI - 10.3934/ipi.2009.3.69
Subject(s) - pixel , orientation (vector space) , computer science , algorithm , monte carlo method , diffraction , data consistency , projection (relational algebra) , detector , consistency (knowledge bases) , function (biology) , optics , mathematics , artificial intelligence , physics , geometry , statistics , telecommunications , evolutionary biology , biology , operating system
An iterative search method is proposed for obtaining orientation maps inside polycrystals from three-dimensional X-ray diffraction (3DXRD) data. In each step, detector pixel intensities are calculated by a forward model based on the current estimate of the orientation map. The pixel at which the experimentally measured value most exceeds the simulated one is identified. This difference can only be reduced by changing the current estimate at a location from a relatively small subset of all possible locations in the estimate and, at each such location, an increase at the identified pixel can only be achieved by changing the orientation in only a few possible ways. The method selects the location/orientation pair indicated as best by a function that measures data consistency combined with prior information on orientation maps. The superiority of the method to a previously published forward projection Monte Carlo optimization is demonstrated on simulated data.
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