Noise Attenuation for CSEM Data via Deep Residual Denoising Convolutional Neural Network and Shift-Invariant Sparse Coding

Noise Attenuation for CSEM Data via Deep Residual Denoising Convolutional Neural Network and Shift-Invariant Sparse Coding

To overcome the interference of noise on the exploration effectiveness of the controlled-source electromagnetic method (CSEM), we improved the deep learning algorithm by combining the denoising convolutional neural network (DnCNN) with the residual network (ResNet), and propose a method based on the...

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Bibliographic Details
Main Authors: Xin Wang, Ximin Bai, Guang Li, Liwei Sun, Hailong Ye, Tao Tong
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Remote Sensing
Subjects:
controlled-source electromagnetic method (CSEM)
denoising convolutional neural network (DnCNN)
residual network (ResNet)
shift-invariant sparse coding (SISC)
deep learning
denoising
Online Access:https://www.mdpi.com/2072-4292/15/18/4456

Internet

https://www.mdpi.com/2072-4292/15/18/4456

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