干旱区生态环境知识资源中心(Arid): Relative Attributes-Based Generative Adversarial Network for Desert Seismic Noise Suppression

Arid

DOI	10.1109/LGRS.2021.3135034
	Relative Attributes-Based Generative Adversarial Network for Desert Seismic Noise Suppression
	Ma, Haitao; Sun, Yu; Wu, Ning; Li, Yue
通讯作者	Wu, N (corresponding author)，Jilin Univ, Coll Commun Engn, Dept Informat, Changchun 130012, Peoples R China.
来源期刊	IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
ISSN	1545-598X
EISSN	1558-0571
出版年	2022
卷号	19
英文摘要	Since seismic data will be interfered with by a host of complicated noise during the acquisition process, the quality of the acquired seismic data is usually poor. The overlap of signals and noise makes it difficult to extract effective signals from desert seismic records. Therefore, the suppression of seismic noise and the retention of seismic signals are key issues in seismic signal processing. In order to improve the quality of the data obtained, we propose an unsupervised relative attributes-based generative adversarial network (RAGAN), which includes a generator, a discriminator, and an attribute match-aware discriminator. By encoding the data of different attributes in seismic records, the denoising task can be regarded as the conversion process of the data corresponding to the attributes. The relative attributes obtained by the difference between the target attribute and the original attribute are used to control the attributes of the data generated by the generator, so as to achieve the purpose of noise suppression. Experimental results of both synthetic and field seismic records show that the proposed method performs better than part of conventional methods.
英文关键词	Generators Noise reduction Training Noise measurement Generative adversarial networks Transforms Convolution Attribute training set relative attributes-based denoising seismic exploration seismic noise suppression
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000742225800011
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/376804
作者单位	[Ma, Haitao; Sun, Yu; Wu, Ning; Li, Yue] Jilin Univ, Coll Commun Engn, Dept Informat, Changchun 130012, Peoples R China
推荐引用方式 GB/T 7714	Ma, Haitao,Sun, Yu,Wu, Ning,et al. Relative Attributes-Based Generative Adversarial Network for Desert Seismic Noise Suppression[J],2022,19.
APA	Ma, Haitao,Sun, Yu,Wu, Ning,&Li, Yue.(2022).Relative Attributes-Based Generative Adversarial Network for Desert Seismic Noise Suppression.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,19.
MLA	Ma, Haitao,et al."Relative Attributes-Based Generative Adversarial Network for Desert Seismic Noise Suppression".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 19(2022).