Efficient Convolutional Sparse Coding Based on Penalized Weighted Least Squares for Seismic Data Denoising

Recently, convolutional sparse coding (CSC) has been successfully applied to seismic data denoising. CSC differs from traditional dictionary learning methods based on patching schemes in that it can directly process the whole data and capture correlations between local neighborhoods. However, the le...

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Bibliographic Details
Published in:	IEEE transactions on geoscience and remote sensing Vol. 62; pp. 1 - 12
Main Authors:	Bai, Min, Yang, Bo, Wu, Juan, Zhou, Zixiang, Cui, Yang, Ma, Zhaoyang, Zeng, Yang
Format:	Journal Article
Language:	English
Published:	New York IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Coding Computational efficiency Computer applications Convolution Convolutional codes Convolutional sparse coding (CSC) Dictionaries Encoding Feature maps Filters Least squares Machine learning Noise reduction penalized weighted least square (PWLS) Random noise Regularization Seismic data seismic data denoising Seismic response Singular value decomposition sparse feature maps Synthetic data
ISSN:	0196-2892, 1558-0644
Online Access:	Get full text
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