| Issue |
EPJ Web Conf.
Volume 226, 2020
Mathematical Modeling and Computational Physics 2019 (MMCP 2019)
|
|
|---|---|---|
| Article Number | 03014 | |
| Number of page(s) | 4 | |
| Section | Mathematical and Computational Support of the Experiments, Computing Tools, and Software Services | |
| DOI | https://doi.org/10.1051/epjconf/202022603014 | |
| Published online | 20 January 2020 | |
https://doi.org/10.1051/epjconf/202022603014
Experimental Data Processing Using Shift Methods
Institute for Nuclear Research (INR), Russian Academy of Sciences,
Moscow,
117312
Russia
★ e-mail: novikov.borodin@gmail.com
Published online: 20 January 2020
The numerical methods of step-by-step and combined shifts are proposed for correction and reconstruction the experimental data convolved with different blur kernels. Methods use a shift technique for the direct deconvolution of experimental data, they are fast and effective for data reconstruction, especially, in the case of discrete measurements. The comparative analysis of proposed methods is presented, inaccuracies of reconstruction with different blur kernels, different volumes of data and noise levels are estimated. There are presented the examples of using the shift methods in processing the statistical data of TOF neutron spectrometers and in planning the proton therapy treatment. The multi-dimensional data processing using shift methods is considered. The examples of renewal the 2D images blurred by uniform motion and distorted with the Gaussian-like blur kernels are presented.
© The Authors, published by EDP Sciences, 2020
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