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1
Published in 2018 at "Surveys in Geophysics"
DOI: 10.1007/s10712-018-9501-3
Abstract: Geophysical data interpolation has attracted much attention in the past decades. While a variety of methods are well established for either regularly sampled or irregularly sampled multi-channel data, an effective method for interpolating extremely sparse…
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Keywords:
sparse geophysical;
geophysical data;
interpolation;
data interpolation ... See more keywords
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0
Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2978173
Abstract: This paper discusses the construction of scattered data interpolation scheme based on rational quartic triangular patches with C1 continuity. The C1 sufficient condition is derived on each adjacent triangle. We employ rational corrected scheme comprising…
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Keywords:
data interpolation;
proposed scheme;
scattered data;
scheme ... See more keywords
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1
Published in 2019 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2019.2914004
Abstract: In this letter, we adapt the geodesic distance-based recursive filter to the sparse data interpolation problem. The proposed technique is general and can be easily applied to any kind of sparse data. We demonstrate its…
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Keywords:
interpolation;
data interpolation;
sparse data;
geodesic distance ... See more keywords
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3
Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3075968
Abstract: The core challenge of seismic data interpolation is how to capture latent spatial-temporal relationships between unknown and known traces in 3-D space. The prevailing tensor-based interpolation schemes seek a globally low-rank approximation to mine the…
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Keywords:
data interpolation;
seismic data;
tensor;
dtae ... See more keywords
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1
Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3110600
Abstract: Seismic data interpolation is a highly ill-posed problem. Therefore, designing an appropriate regulating method, aiming to reduce multi-solutions, is of utmost importance. Sparse and low-rank priors or constraints, which consider certain kinds of redundant data…
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Keywords:
low rank;
sparse low;
data interpolation;
seismic data ... See more keywords
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1
Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3180200
Abstract: The undersampled seismic data may suffer from the degraded quality and pose negative impacts on subsequent processing procedures. Seismic data interpolation is a cost-saving technique to obtain regular and high-density data in the modern seismological…
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Keywords:
data interpolation;
shannon entropy;
interpolation;
seismic data ... See more keywords
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2
Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3234601
Abstract: Seismic data interpolation is an indispensable part of seismic data processing. In recent years, deep-learning-based interpolation algorithms for seismic data have become popular due to their high accuracy. However, a considerable amount of work has…
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Keywords:
self supervised;
interpolation;
data interpolation;
regeneration prior ... See more keywords