Laser & Optoelectronics Progress, Volume. 58, Issue 6, 610004(2021)
X-Ray Image Reconstruction Based on Hierarchical Model and Low-Rank Approximation
Fig. 1. Reconstruction results of FTO variable density image at 3% noise level. (a) Noise-containing optical path image; (b) original image; (c) GPSR; (d) PNM_WLSA; (e) LRIS_ Gamma; (f) LRIS_ Jefferys; (g) SPA; (h) proposed method
Fig. 2. Reconstruction results of FTO constant density image at 3% noise level. (a) Noise-containing optical path image; (b) original image; (c) GPSR; (d) PNM_WLSA; (e) LRIS_ Gamma; (f) LRIS_ Jefferys; (g) SPA; (h) proposed method
Fig. 3. Real X-ray images and reconstructed results. (a) Real X-ray images; (b) reconstruction results
Fig. 4. Reconstruction results of different algorithms. (a) Regional profile diagram of tin column (CL3); (b) regional profile diagram of tin disk (DR1)
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Wang Jiayu, Xu Jinxin, Li Qingwu. X-Ray Image Reconstruction Based on Hierarchical Model and Low-Rank Approximation[J]. Laser & Optoelectronics Progress, 2021, 58(6): 610004
Category: Image Processing
Received: Jul. 31, 2020
Accepted: --
Published Online: Mar. 11, 2021
The Author Email: Qingwu Li (li_qingwu@163.com)