干旱区生态环境知识资源中心(Arid): Deep Residual Encoder-Decoder Networks for Desert Seismic Noise Suppression

Arid

DOI	10.1109/LGRS.2019.2925062
	Deep Residual Encoder-Decoder Networks for Desert Seismic Noise Suppression
	Ma, Haitao; Yao, Haiyang; Li, Yue; Wang, Hongzhou
通讯作者	Li, Yue
来源期刊	IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
ISSN	1545-598X
EISSN	1558-0571
出版年	2020
卷号	17 期号:3 页码:529-533
英文摘要	The convolutional neural network (CNN) has achieved excellent performance in many fields, which has attracted much attention. CNN is a kind of feedforward neural network with convolution computation and depth structure. In this letter, aiming at the intense interference of seismic exploration noise in the desert of China, a desert seismic noise reduction system based on deep residual encoder-decoder network is proposed. In order to extract the characteristics and variation law of desert seismic noise, a noise set containing a large number of desert seismic noise is utilized for training the network so that the network forms the end-to-end mapping between the noisy records and the noise. Consequently, the effective signals are obtained by subtracting noise from the noisy records so as to achieve a satisfactory denoising performance. Compared with the traditional random noise suppression methods, the advantages of the proposed method are fully demonstrated in the processing of the synthetic records and the field records. Especially when the signal-to-noise ratio (SNR) is very low, this proposed method can still have a very good denoising effect.
英文关键词	Noise reduction Signal to noise ratio Deconvolution Convolution Noise measurement Training Deep learning Convolutional neural network (CNN) deep learning denoising desert seismic noise residual learning seismic exploration
类型	Article
语种	英语
国家	Peoples R China
收录类别	SCI-E
WOS记录号	WOS:000521960200034
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/2XILL650/314710
作者单位	Jilin Univ, Dept Informat, Coll Commun Engn, Changchun 130012, Peoples R China
推荐引用方式 GB/T 7714	Ma, Haitao,Yao, Haiyang,Li, Yue,et al. Deep Residual Encoder-Decoder Networks for Desert Seismic Noise Suppression[J],2020,17(3):529-533.
APA	Ma, Haitao,Yao, Haiyang,Li, Yue,&Wang, Hongzhou.(2020).Deep Residual Encoder-Decoder Networks for Desert Seismic Noise Suppression.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,17(3),529-533.
MLA	Ma, Haitao,et al."Deep Residual Encoder-Decoder Networks for Desert Seismic Noise Suppression".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 17.3(2020):529-533.