Fast Dictionary Learning for High-Dimensional Seismic Reconstruction

A sparse dictionary is more adaptive than a sparse fixed-basis transform since it can learn the features directly from the input data in a data-driven way. However, learning a sparse dictionary is time-consuming because a large number of iterations are required in order to obtain the dictionary atom...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing Jg. 59; H. 8; S. 7098 - 7108
Hauptverfasser:	Wang, Hang, Chen, Wei, Zhang, Quan, Liu, Xingye, Zu, Shaohuan, Chen, Yangkang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.08.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Atomic properties Computational efficiency Computer applications Computing costs Decomposition Dictionaries Dictionary learning (DL) Encoding Glossaries high-dimensional problem Image reconstruction Learning Mathematical model Seismic data seismic data reconstruction signal processing Singular value decomposition Sparse matrices Transforms
ISSN:	0196-2892, 1558-0644
Online-Zugang:	Volltext
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