Data related to super-resolution imaging based on cold neutron beam flow

The dataset consists of all the data in the process of applied research, experimental measurement, reconstruction and calculation, inspection and testing, including raw data that can be used for scientific research activities, and derived data at all levels obtained through pre-processing, computational processing, and analyses and comparisons.Specifically, the dataset contains:1. the main devices of the system for neutron imaging. This includes the 6LiF-ZnS scintillator screen, reflector, optical lens set, image intensifier (image intensifier), and sCMOS camera. The physical design and structural features of the device are described, and the relevant devices include: beamline, main shutter, aperture selector, first flight tube, second flight tube, beam control system, four-dimensional scanning, imaging system, and beam terminator.2. The computational steps of the algorithm are given in the data, including the specific method schematic of subtracting the noise background, median/Gaussian filtering, light spot segmentation, and local extreme value calculation.3. Raw data collected in the experiment: neutron signal and noise signal were collected when the reactor power was near 10 MW. Neutron detection data included fixed noise data, random noise data, other noise data, neutron detection signal data, and superimposed signal data.4. conventional integral imaging data obtained by post-processing of the experimental data, and the grey scale distribution of the region of interest of its image.5. super-resolution imaging results of the experimental data, specifically including: (1) center-of-mass algorithm reconstruction results; (2) center-of-mass algorithm reconstruction results, the grey scale distribution of the resolution stripe; (3) median-filtered center-of-mass algorithm reconstruction results; (4) median-filtered center-of-mass algorithm reconstruction results, the grey scale distribution of the resolution stripe; (5) median-filtered polar algorithm reconstruction results; (6) median-filtered polar algorithm reconstruction results; (7) median-filtered polar algorithm reconstruction results; and (8) median-filtered polar algorithm reconstruction results. results; (7) the grey scale distribution of the resolution stripe; (7) the reconstruction results of Gaussian filtering extreme value algorithm; (8) the grey scale distribution of the resolution stripe in the reconstruction results of Gaussian filtering extreme value algorithm.6. Comparison between experimental raw data and computationally processed data, including: (1) grey scale distribution of raw data; (2) grey scale distribution after filtering; (3) grey scale distribution after spot segmentation; (4) grey scale distribution of reconstruction results.Translated with DeepL.com (free version)