中国激光, 2018, 45 (10): 1014001, 网络出版: 2018-10-12
压缩感知三维重建算法控制参数对太赫兹数字全息再现的影响 
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Influences of Compressive Sensing 3D Reconstruction Algorithm Control Parameters on Terahertz Digital Holography Reconstruction
图 & 表
图 2. 不同情况下的断层仿真场景。(a)理想情况;(b)高斯噪声方差为0.0005;(c)高斯噪声方差为0.001
Fig. 2. Sample simulation scenario obtained under different conditions. (a) Ideal case; (b) a case with Gaussian noise variance of 0.0005; (c) a case with Gaussian noise variance of 0.001
图 3. 不同情况下的仿真全息图。(a)理想情况;(b)高斯噪声方差为0.0005;(c)高斯噪声方差为0.001
Fig. 3. Simulation holograms obtained under different conditions. (a) Ideal case; (b) a case with Gaussian noise variance of 0.0005; (c) a case with Gaussian noise variance of 0.001
图 5. τ=0.1时不同迭代次数的再现结果。(a) t=50; (b) t=100; (c) t=150; (d) t=200; (e) t=250; (f) t=300; (g) t=350; (h) t=400
Fig. 5. Reconstruction results for different iteration times when τ=0.1. (a) t=50; (b) t=100; (c) t=150; (d) t=200; (e) t=250; (f) t=300; (g) t=350; (h) t=400
图 6. 理想情况下,迭代次数与(a) PSNR、(b) MSSIM的关系
Fig. 6. Relationship between number of iteration and (a) PSNR or (b) MSSIM under ideal condition
图 7. 理想情况下,稀疏限制参数与(a) PSNR、(b) MSSIM的关系
Fig. 7. Relationship between sparse restriction parameter and (a) PSNR or (b) MSSIM under ideal condition
图 8. 理想情况下的再现图像。(a)样本“T”;(b)样本“H”
Fig. 8. Ideal reconstructed images. (a) “T” sample; (b) “H” sample
图 9. 高斯噪声方差为0.0005时,稀疏限制参数与(a) PSNR、(b) MSSIM的关系
Fig. 9. Relationship between sparse restriction parameter and (a) PSNR or (b) MSSIM when Gaussian noise variance is 0.0005
图 10. 高斯噪声方差为0.0005时,稀疏限制参数与(a) PSNR、(b) MSSIM的关系(0.05≤τ≤0.14)
Fig. 10. Relationship between sparse restriction parameter (0.05≤τ≤0.14) and (a) PSNR or (b) MSSIM when Gaussian noise variance is 0.0005
图 11. 高斯噪声方差为0.0005时,迭代次数与(a) PSNR、(b) MSSIM的关系
Fig. 11. Relationship between number of iteration and (a) PSNR or (b) MSSIM when Gaussian noise variance is 0.0005
图 12. 高斯噪声方差为0.0005时的最佳再现图像。(a)样本“T”;(b)样本“H”
Fig. 12. The best reconstructed images with Gaussian noise variance of 0.0005. (a) “T” sample; (b) “H” sample
图 13. 高斯噪声方差为0.001时,稀疏限制参数与(a) PSNR、(b) MSSIM的关系
Fig. 13. Relationship between sparse restriction parameter and (a) PSNR or (b) MSSIM when Gaussian noise variance is 0.0001
图 14. 高斯噪声方差为0.001时,迭代次数与(a) PSNR、(b) MSSIM的关系
Fig. 14. Relationship between number of iteration values and (a) PSNR or (b) MSSIM when Gaussian noise variance is 0.001
图 15. 高斯噪声的方差为0.001时的最佳再现结果。(a)样本“T”;(b)样本“H”
Fig. 15. The best reconstructed images with Gaussian noise variance of 0.001. (a) “T” sample; (b) “H” sample
表 1仿真结果汇总
Table1. Summary of simulation results
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袁静, 李琦, 巩文盼. 压缩感知三维重建算法控制参数对太赫兹数字全息再现的影响[J]. 中国激光, 2018, 45(10): 1014001. Yuan Jing, Li Qi, Gong Wenpan. Influences of Compressive Sensing 3D Reconstruction Algorithm Control Parameters on Terahertz Digital Holography Reconstruction[J]. Chinese Journal of Lasers, 2018, 45(10): 1014001.
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