Reconstruction of Stack Plume Based on Imaging Differential Absorption Spectroscopy and Compressed Sensing
ZHONG Ming-yu1, 2, 3, ZHOU Hai-jin2, SI Fu-qi2*, WANG Yu2, DOU Ke2, SU Jing-ming1, 2, 3
1. College of Electrical and Information Engineering, Anhui University of Science and Technology, Huainan 232001, China
2. Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
3. University of Science and Technology of China, Hefei 230031, China
Abstract：The quality of computed tomography image of stack plume has two limits. Oneof the limitations isthe temporal resolution of data acquisition of remote sensing instrument. The conventional remote sensing instrument used for tomography is an multi-axis differential optical absorption spectrometer. Limited by its’ speed of data acquisition, the temporal resolution of the reconstructed image is low. The other limitation is the insufficient data acquired from remote sensing instruments. Algebraic reconstruction algorithms and iterative statistical algorithms are usually used in the reconstruction, but the reconstructed images have a low resolution and plenty of artifacts. To overcome the first limitation, data acquisition system in this paper is composed of imaging differential optical absorption spectrum technique. Compared with the system composed of the multi-axis differential optical absorption spectrum, the system’s temporal resolution increases above 160 times. An algorithm based on compressed sensing and a low third derivative model is introduced to overcome the second limitation. The algorithm is called projection on convex sets-low the third derivative method, which is POCS-LTD in short. The proposed algorithm belongs to gradient projection for sparse reconstruction algorithms, which is divide into two steps: projection and total variation iteration. In the process of projection, the algebraic reconstruction algorithm is used to make the reconstructed image conform to the projection equation, and the optimization algorithm is used in the process of total variation iteration. In the process of the total variation, the normalized value of the low third order derivative model is used as the iterative direction of the optimization algorithm, and the module of the difference between the result of the previous iteration and the present projection operation is used as the iterative step. According to nearness, the reconstructed images are evaluated, the relative difference of maximum and concordance correlation factor by numerical simulation. The numerical simulation shows that the proposed algorithm has good error resist,and reduces nearness by 80% compared with the traditional low third derivative method. The method is used to reconstruct the plume by the data gets from the field campaign. A clear plume and suppression of artifacts can be seen from the reconstructed image. The data acquisition system and algorithm introduced in this paper promote temporal resolution and reduce artifacts of the reconstructed images, and improve the technique’s practicability.
钟鸣宇，周海金，司福祺，王 煜，窦 科，苏静明. 基于成像差分吸收光谱技术和压缩感知理论的烟囱烟羽断层重建研究[J]. 光谱学与光谱分析, 2021, 41(06): 1708-1712.
ZHONG Ming-yu, ZHOU Hai-jin, SI Fu-qi, WANG Yu, DOU Ke, SU Jing-ming. Reconstruction of Stack Plume Based on Imaging Differential Absorption Spectroscopy and Compressed Sensing. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(06): 1708-1712.
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