15 November 2017 X-ray counting imaging based on spherical collimation
Author Affiliations +
Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 106053U (2017) https://doi.org/10.1117/12.2295871
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China
Abstract
Aiming at the difficulty in X-ray focusing, small field of view and the low sensitivity for the X-ray imaging, a spherically collimated X-ray counting imaging method was proposed based on the concept of single-pixel camera. The spatial X-ray star maps that are sparse in the airspace were measured under the function of binary sparse observation matrix, and reconstructed rapidly by the use of TVAL3 algorithm. Finally, a series of simulations were designed to evaluate the performance of the reconstruction in Peak Signal to Noise Ratio (PSNR), Bhattacharyya Coefficient and Pearson Correlation Coefficient (PCC). The results demonstrate that the PSNR and PCC of the reconstructed image are respectively 27.1992 and 0.94273 for the sparse ratio 0.05.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
H. F. Sun, H. F. Sun, T. Li, T. Li, H. Y. Fang, H. Y. Fang, J. Y. Su, J. Y. Su, S. P. Cong, S. P. Cong, } "X-ray counting imaging based on spherical collimation", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 106053U (15 November 2017); doi: 10.1117/12.2295871; https://doi.org/10.1117/12.2295871
PROCEEDINGS
8 PAGES


SHARE
Back to Top