GPR denoising via shearlet transformation and a data‐driven tight frame-Reference-Cited by-同舟云学术

GPR denoising via shearlet transformation and a data‐driven tight frame

Published:2022-05-30 Issue:4 Volume:20 Page:398-418
ISSN:1569-4445
Container-title:Near Surface Geophysics
language:en
Short-container-title:Near Surface Geophysics

Author:

Zhang Liang¹²^ORCID,Tang Jingtian¹²,Li Yaqi³,Liu Zhengguang¹²,Chen Wenjie⁴,Li Guang⁵

Affiliation:

1. School of Geosciences and Info‐Physics Central South University Changsha Hunan 410083 People's Republic of China

2. Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of Education (Central South University) Changsha Hunan 410083 People's Republic of China

3. School of Police Administration People's Public Security University of China Beijing 100038 People's Republic of China

4. College of Information Technology Guangxi Police College Nanning Guangxi 530028 People's Republic of China

5. School of Geophysics and Measurement‐control Technology East China University of Technology Nanchang Jiangxi 330013 People's Republic of China

Publisher

Wiley

Subject

Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nsg.12212

Reference42 articles.

1. Surface Defects Classification of Hot-Rolled Steel Strips Using Multi-directional Shearlet Features

2. Convergence analysis for iterative data-driven tight frame construction scheme

3. Clutter Elimination and Random-Noise Denoising of GPR Signals Using an SVD Method Based on the Hankel Matrix in the Local Frequency Domain

4. Data-driven tight frame construction and image denoising

5. Double-sparsity dictionary for seismic noise attenuation

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