Ground-Based IDOAS De-Striping by Weighted Unidirectional Variation

doi:10.3964/j.issn.1000-0593(2022)02-0627-07

	Ground-Based IDOAS De-Striping by Weighted Unidirectional Variation
	Xi Liang 1,2; Si Fu-qi 1; Jiang Yu 1; Zhou Hai-jin 1; Qiu Xiao-han 1; Chang Zhen 1
刊名	SPECTROSCOPY AND SPECTRAL ANALYSIS
	2022-02-01
卷号	42
关键词	Imaging differential optical absorption spectroscopy Stripe noise Variation Optical remote sensing
ISSN号	1000-0593
DOI	10.3964/j.issn.1000-0593(2022)02-0627-07
通讯作者	Si Fu-qi(sifuqi@aiofm.ac.cn)
英文摘要	Imaging differential optical absorption spectroscopy technology (IDOAS) combines imaging spectroscopy and differential optical absorption spectroscopy. The acquired data of IDOAS instruments are so-called hyperspectral cube with two spatial dimensions and a spectral one. After DOAS analysis of the original data, two-dimensional trace gas distributions can be resolved. For ground-based IDOAS instruments, the imaging capability is achieved through the stepwise rotation of the motor in the horizontal direction, which can be used to identify the emission sources of polluting gases and monitor the transmission of pollution. However, similar to other imaging spectroscopy instruments, ground-based IDOAS instruments are also prone to stripe noise, producing corresponding pseudo-structures and affecting subsequent information extraction and data analysis. Several de-striping algorithms have been applied for space-borne and airborne sensors, including homogeneous reference area correction method, transmission model simulation method, frequency domain filtering method, polynomial fitting method, which are not fully applicable to ground-based instruments. Here we present a de-striping algorithm based on a weighted unidirectional variation model. This algorithm first obtains a weight matrix that characterizes the blocked area through adaptive threshold segmentation, then utilizes the unidirectionality and sparsity of the strip noise to establish the optimization model, which is solved iteratively by using the alternating direction method multipliers technique. To test the performance of the de-striping algorithm, simulated experiments were performed using various cases including sparse, dense, periodic, random, whole-line, partial, single-line, multi-line stripe noise. Corresponding results prove that this algorithm can effectively remove typical stripe noise, with good performances in visual and four full-reference evaluations. Ground-based IDOAS observations were carried out in Leshan, Sichuan province, in the summer of 2018. In this experiment, the IDOAS instrument provided a full-azimuthal coverage (360 degrees) and a 30 degrees vertical coverage around the measurement site. The acquisition time of a full-panoramic image was about 15 min when the integration time was set to 500 ms. The final panoramic views of NO2 and SO2 columns consist of 48 vertical and 360 angles on the horizontal axis. According to the real data results, the stripe noise changed greatly for different gases at different times. After de-striping by this weighted variation algorithm, the stripe noise in the NO2 and SO2 columns reduced greatly without over-smoothing. Experimental results of the real data demonstrate that this algorithm is suitable for de-striping of ground-based IDOAS data.
WOS关键词	RETRIEVAL ALGORITHM ; NO2
WOS研究方向	Spectroscopy
语种	英语
出版者	OFFICE SPECTROSCOPY & SPECTRAL ANALYSIS
WOS记录号	WOS:000763774300047
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/128215]
专题	中国科学院合肥物质科学研究院
通讯作者	Si Fu-qi
作者单位	1.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei Inst Phys Sci, Hefei 230031, Peoples R China 2.Univ Sci & Technol China, Hefei 230026, Peoples R China
推荐引用方式 GB/T 7714	Xi Liang,Si Fu-qi,Jiang Yu,et al. Ground-Based IDOAS De-Striping by Weighted Unidirectional Variation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS,2022,42.
APA	Xi Liang,Si Fu-qi,Jiang Yu,Zhou Hai-jin,Qiu Xiao-han,&Chang Zhen.(2022).Ground-Based IDOAS De-Striping by Weighted Unidirectional Variation.SPECTROSCOPY AND SPECTRAL ANALYSIS,42.
MLA	Xi Liang,et al."Ground-Based IDOAS De-Striping by Weighted Unidirectional Variation".SPECTROSCOPY AND SPECTRAL ANALYSIS 42(2022).