Efficient Denoising of Multidimensional GPR Data Based on Fast Dictionary Learning

Efficient Denoising of Multidimensional GPR Data Based on Fast Dictionary Learning

Denoising plays a fundamental role in ground penetrating radar (GPR) data processing and determines the effect of anomaly extraction, inversion imaging, and other subsequent processing. In recent years, the sparse dictionary representation method k-singular value decomposition (K-SVD) based on K-mea...

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Bibliographic Details
Main Authors: Deshan Feng, Li He, Xun Wang, Yougan Xiao, Guoxing Huang, Liqiong Cai, Xiaoyong Tai
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Dictionary learning
ground penetrating radar (GPR)
K-singular value decomposition (K-SVD)
noise attenuation
sparse representation
sequential generalized K-means (SGK)
Online Access:https://ieeexplore.ieee.org/document/10438015/

Internet

https://ieeexplore.ieee.org/document/10438015/

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