开路傅里叶变换红外光谱层析重建算法仿真 下载: 1094次
Simulation of Tomographic Reconstruction Algorithms for Open-Path Fourier Transform Infrared Spectroscopy
1 中国科学院安徽光学精密机械研究所环境光学与技术重点实验室, 安徽 合肥 230031
2 中国科学技术大学, 安徽 合肥 230026
图 & 表
图 1. 重建模型
Fig. 1. Reconstruction model
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图 2. (a)光路布置方式与(b)单峰气体浓度场
Fig. 2. (a) Light path arrangement and (b) single-peak gas concentration field
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图 3. 松弛因子α对重建结果的影响。(a)对逼近度A的影响;(b)对相关系数R的影响
Fig. 3. Effect of relaxation factors α on reconstruction results. (a) Effect on nearness A; (b) effect on correlation coefficient R
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图 4. 不同网格分辨率下的重建结果。(a)~(c) ART;(d)~(f) MLEM
Fig. 4. Reconstruction results under different grid resolutions. (a)-(c) ART; (d)-(f) MLEM
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图 5. 不同浓度场下的重建结果。(a)单峰,原始浓度场;(b)双峰,原始浓度场;(c)单峰,ART算法;(d)双峰,ART算法;(e)单峰,MLEM算法;(f)双峰,MLEM算法
Fig. 5. Reconstruction results under different concentration fields. (a) Original concentration field of single peak; (b) original concentration field of double peak; (c) single peak, ART algorithm; (d) double peak, ART algorithm; (e) single peak, MLEM algorithm; (f) double peak, MLEM algorithm
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图 6. 不同噪声水平下的误差分析。(a) A;(b) R
Fig. 6. Error analysis under different noise levels. (a) A; (b) R
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表 1不同网格分辨率下的整体重建精度
Table1. Overall reconstruction accuracy under different grid resolutions
Resolution | Nearness A | Correlation coefficient R | Running time T /s | | |
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ART | MLEM | ART | MLEM | ART | MLEM |
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5×5 | 0.236 | 0.073 | 0.972 | 0.998 | 0.153 | 0.061 | 7×7 | 0.227 | 0.056 | 0.978 | 0.999 | 0.185 | 0.064 | 10×10 | 0.197 | 0.055 | 0.981 | 0.999 | 0.236 | 0.066 |
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表 2不同网格分辨率下的细节重建精度
Table2. Detail reconstruction accuracy under different grid resolutions
Resolution | Peak value /(mg·m-3) | Peak error /% | Peak location error /m | | |
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ART | MLEM | ART | MLEM | ART | MLEM |
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5×5 | 39.7 | 45.3 | 20.60 | 9.40 | 4 | 4 | 7×7 | 38.7 | 44.6 | 22.60 | 10.80 | 5 | 5 | 10×10 | 39.1 | 45.6 | 21.80 | 8.80 | 4 | 4 |
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表 3不同源位置的整体重建精度
Table3. Overall reconstruction accuracy of different source locations
Source location | Nearness A | Correlation coefficient R | Running time T /s | | |
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ART | MLEM | ART | MLEM | ART | MLEM |
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(75,25) | 0.167 | 0.044 | 0.986 | 0.999 | 0.219 | 0.063 | (53,53) | 0.200 | 0.057 | 0.980 | 0.998 | 0.218 | 0.064 | (30,70) | 0.180 | 0.051 | 0.983 | 0.999 | 0.217 | 0.067 | Mean | 0.182 | 0.049 | 0.983 | 0.999 | 0.218 | 0.065 |
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表 4不同源位置的细节重建精度
Table4. Detail reconstruction accuracy of different source locations
Source location | Peak value /(mg·m-3) | Peak error /% | Peak location error /m | | |
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ART | MLEM | ART | MLEM | ART | MLEM |
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(75,25) | 41.3 | 47.4 | 17.40 | 5.20 | 0 | 0 | (53,53) | 38.5 | 45.9 | 23.00 | 8.20 | 3.0 | 3.0 | (30,70) | 37.7 | 42.2 | 24.60 | 15.60 | 7.0 | 7.0 | Mean | 39.2 | 45.2 | 21.67 | 9.67 | 3.3 | 3.3 |
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表 5不同浓度场下的整体重建精度
Table5. Overall reconstruction accuracy of different concentration fields
Source location | Nearness A | Correlation coefficient R | Running time T /s | | |
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ART | MLEM | ART | MLEM | ART | MLEM |
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(55,75) | 0.177 | 0.044 | 0.984 | 0.999 | 0.233 | 0.063 | (35,55),(75,55) | 0.263 | 0.069 | 0.964 | 0.998 | 0.228 | 0.065 |
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表 6不同浓度场性质下的细节重建精度
Table6. Detail reconstruction accuracy under different concentration fields
Source location | Peak value /(mg·m-3) | Mean peak error /% | Peak location | | |
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ART | MLEM | ART | MLEM | ART | MLEM |
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(55,75) | 64.90 | 75.40 | 17.40 | 5.20 | (55,75) | (55,75) | (35,55),(75,55) | 49.40,72.30 | 50.30,91.10 | 14.45 | 4.75 | (35,55),(75,55) | (35,55),(75,55) |
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表 7不同噪声水平下两种算法的重建评价指标
Table7. Evaluation indexes of reconstruction under different noise levels
Noise level | Nearness A | Correlation coefficient R | |
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ART | MLEM | ART | MLEM |
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0.3 | 0.402 | 0.352 | 0.929 | 0.936 | 0.5 | 0.656 | 0.527 | 0.872 | 0.885 | 0.7 | 1.134 | 1.498 | 0.706 | 0.585 |
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邓矗岭, 童晶晶, 高闽光, 李相贤, 李妍, 韩昕, 刘文清. 开路傅里叶变换红外光谱层析重建算法仿真[J]. 光学学报, 2019, 39(7): 0707001. Chuling Deng, Jingjing Tong, Minguang Gao, Xiangxian Li, Yan Li, Xin Han, Wenqing Liu. Simulation of Tomographic Reconstruction Algorithms for Open-Path Fourier Transform Infrared Spectroscopy[J]. Acta Optica Sinica, 2019, 39(7): 0707001.