Laser & Optoelectronics Progress, Volume. 55, Issue 11, 111103(2018)
Sparse Image Reconstruction Based on Improved Total Generalized Variation
Figures & Tables(13)
Fig. 2. Image data used in the test. (a) Sheep-Logan image; (b) Forbild-Head image; (c) Forbild-Abdomen image
Fig. 3. ROI regions of the test images. (a) Sheep-Logan image; (b) Forbild-Head image; (c) Forbild-Abdomen image
Fig. 4. Reconstructed image and ROI comparison of different algorithms in finite angle (Sheep-Logan). (a) Original image; (b) L1-Bregman algorithm; (c) TV-ADM algorithm; (d) TVAL3 algorithm; (e) TGV-ADM algorithm; (f) proposed algorithm
Fig. 5. Reconstructed image and ROI comparison of different algorithms in finite angle (Forbild-Head). (a) Original image; (b) L1-Bregman algorithm; (c) TV-ADM algorithm; (d) TVAL3 algorithm; (e) TGV-ADM algorithm; (f) proposed algorithm
Fig. 6. Reconstructed image and ROI comparison of different algorithms in finite angle (Forbild-Abdomen). (a) Original image; (b) L1-Bregman algorithm; (c) TV-ADM algorithm; (d) TVAL3 algorithm; (e) TGV-ADM algorithm; (f) proposed algorithm
Fig. 7. Reconstructed image and ROI comparison of different algorithms in sparse angle (Sheep-Logan). (a) Original image; (b) L1-Bregman algorithm; (c) TV-ADM algorithm; (d) TVAL3 algorithm; (e) TGV-ADM algorithm; (f) proposed algorithm
Fig. 8. Reconstructed image and ROI comparison of different algorithms in sparse angle (Forbild-Head). (a) Original image; (b) L1-Bregman algorithm; (c) TV-ADM algorithm; (d) TVAL3 algorithm; (e) TGV-ADM algorithm; (f) proposed algorithm
Fig. 9. Reconstructed image and ROI comparison of different algorithms in sparse angle (Forbild-Abdomen). (a) Original image; (b) L1-Bregman algorithm; (c) TV-ADM algorithm; (d) TVAL3 algorithm; (e) TGV-ADM algorithm; (f) proposed algorithm
Fig. 10. Comparison of vertical cross-sectional views of 135th column of each reconstruction image. (a) Sheep-Logan image; (b) Forbild-Head image; (c) Forbild-Abdomen image
Table 1. Initialization parameters
View tableTable 1. Initialization parameters
Parameter β μi (i =1,2,3)γ α 0α 1Value 64 32 1 0.2 2
Table 2. Comparison of objective evaluation parameters of reconstructed images of various algorithms under finite projection angle
View tableTable 2. Comparison of objective evaluation parameters of reconstructed images of various algorithms under finite projection angle
Algorithm Image SSIM PSNR /dB RMSE Time /s L1-Bregman Sheep-Logan 0.549 15.748 0.163 10.969 Forbild-Head 0.430 13.175 0.219 11.063 Forbild-Abdomen 0.535 15.672 0.165 11.328 TV-ADM Sheep-Logan 0.891 22.203 0.078 16.467 Forbild-Head 0.893 21.916 0.080 16.453 Forbild-Abdomen 0.967 33.024 0.022 15.781 TVAL3 Sheep-Logan 0.894 22.807 0.073 19.625 Forbild-Head 0.899 23.072 0.070 20.109 Forbild-Abdomen 0.968 33.643 0.021 22.234 TGV-ADM Sheep-Logan 0.899 25.039 0.056 70.016 Forbild-Head 0.935 27.420 0.043 69.594 Forbild-Abdomen 0.967 35.312 0.018 68.609 Proposed Sheep-Logan 0.903 26.091 0.054 150.682 Forbild-Head 0.954 29.229 0.035 149.531 Forbild-Abdomen 0.977 39.231 0.011 147.000
Table 3. Comparison of objective evaluation parameters of reconstructed images of various algorithms under sparse projection angle
View tableTable 3. Comparison of objective evaluation parameters of reconstructed images of various algorithms under sparse projection angle
Algorithm Image SSIM PSNR /dB RMSE Time /s L1-Bregman Sheep-Logan 0.619 17.449 0.134 11.625 Forbild-Head 0.185 14.441 0.190 11.078 Forbild-Abdomen 0.543 16.340 0.152 12.953 TV-ADM Sheep-Logan 0.995 45.429 0.005 16.797 Forbild-Head 0.993 39.136 0.011 16.531 Forbild-Abdomen 0.981 36.339 0.015 17.250 TVAL3 Sheep-Logan 0.995 46.075 0.005 20.953 Forbild-Head 0.995 43.074 0.007 20.234 Forbild-Abdomen 0.985 38.522 0.012 22.000 TGV-ADM Sheep-Logan 0.991 44.582 0.006 69.031 Forbild-Head 0.995 43.810 0.006 67.406 Forbild-Abdomen 0.978 39.608 0.011 71.922 Proposed Sheep-Logan 0.999 50.018 0.003 144.250 Forbild-Head 0.999 52.172 0.003 146.359 Forbild-Abdomen 0.991 39.930 0.010 149.141
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Xiaozheng Ban, Zhihua Li, Beibei Li, Minda Xu. Sparse Image Reconstruction Based on Improved Total Generalized Variation[J]. Laser & Optoelectronics Progress, 2018, 55(11): 111103
Paper Information
Category: Imaging Systems
Received: Apr. 23, 2018
Accepted: Jun. 8, 2018
Published Online: Aug. 14, 2019
The Author Email: Zhihua Li (jswxzhli@aliyun.com)
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