• Laser & Optoelectronics Progress
  • Vol. 59, Issue 23, 2310001 (2022)
Qianghua Chen1,*, Jinhong Ding1, Sheng Zhou1, Wenyuan Han1..., Lü Hongbo1, Qiguo Sun1, Xiangyue Kong2 and Huifu Luo3|Show fewer author(s)
Author Affiliations
  • 1School of Mechanical and Materials Engineering, North China University of Technology, Beijing 100144, China
  • 2The 11th Research Institute of China Electronics Technology Corporation, Beijing 100016, China
  • 3School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
  • show less
    DOI: 10.3788/LOP202259.2310001 Cite this Article Set citation alerts
    Qianghua Chen, Jinhong Ding, Sheng Zhou, Wenyuan Han, Lü Hongbo, Qiguo Sun, Xiangyue Kong, Huifu Luo. Tomographic Image Reconstruction Method Combining Exponential Filtering Inverse Projection Reconstruction and Iterative Reconstruction Algorithms[J]. Laser & Optoelectronics Progress, 2022, 59(23): 2310001 Copy Citation Text show less
    Schematic diagram of two-dimensional Radon transform
    Fig. 1. Schematic diagram of two-dimensional Radon transform
    Schematic diagram of iterative EF inverse projection reconstruction algorithm
    Fig. 2. Schematic diagram of iterative EF inverse projection reconstruction algorithm
    Schematic diagram of d and r changing with C
    Fig. 3. Schematic diagram of d and r changing with C
    Comparison of reconstructed images between EF inverse projection and iterative EF inverse projection algorithms.(a) EF inverse projection reconstructed image; (b) grey value comparison of the 128th line for EF inverse projection algorithm; (c) iterative EF inverse projection reconstructed image; (d) corresponding grey value comparison of the 128th line for iterative EF inverse projection algorithm
    Fig. 4. Comparison of reconstructed images between EF inverse projection and iterative EF inverse projection algorithms.(a) EF inverse projection reconstructed image; (b) grey value comparison of the 128th line for EF inverse projection algorithm; (c) iterative EF inverse projection reconstructed image; (d) corresponding grey value comparison of the 128th line for iterative EF inverse projection algorithm
    Diagram of the refractive index field measurement system based on laser polarization tomography for algorithm verification
    Fig. 5. Diagram of the refractive index field measurement system based on laser polarization tomography for algorithm verification
    Reconstruction results of 3D refraction field. (a) By EF inverse projection reconstruction algorithm; (b) by iterative EF inverse projection reconstruction algorithm
    Fig. 6. Reconstruction results of 3D refraction field. (a) By EF inverse projection reconstruction algorithm; (b) by iterative EF inverse projection reconstruction algorithm
    Comparison of refractive index results got by two reconstruction algorithms and calibration results of the instrument
    Fig. 7. Comparison of refractive index results got by two reconstruction algorithms and calibration results of the instrument
    Filter functionExpression
    Ram-Lak17Hω=ωrectω/2R
    Shepp-Logan20Hω=ω2Rsinπω/2R/πωrectω/2R
    Hamming17Hω=ω0.54+0.46cosπω/2Rrectω/2R
    Hann17Hω=ω0.5+0.5cosπω/2Rrectω/2R
    Cosine15Hω=ωcosπω/2Rrectω/2R
    EF17Hω=ωexp-Cω31+ω2rectω/2R
    Table 1. Expressions of each filter function
    Filter functiondr
    Ram-Lak0.7828351.257933
    Shepp-Logan0.6896651.101311
    Hamming0.4293500.601243
    Hann0.4086540.551063
    Cosine0.4804480.715729
    EF0.3885050.465358
    Table 2. d and r of reconstruction results by different filter functions
    Reconstruction algorithmdrTime /s
    EF inverse projection algorithm0.3885050.465358112
    Presented algorithm0.3781900.374133346
    Table 3. d and r of reconstruction results of EF inverse projection reconstruction algorithm and presented algorithm
    Qianghua Chen, Jinhong Ding, Sheng Zhou, Wenyuan Han, Lü Hongbo, Qiguo Sun, Xiangyue Kong, Huifu Luo. Tomographic Image Reconstruction Method Combining Exponential Filtering Inverse Projection Reconstruction and Iterative Reconstruction Algorithms[J]. Laser & Optoelectronics Progress, 2022, 59(23): 2310001
    Download Citation