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PandRS(96), No. 1, 2014, pp. 224-235.
Elsevier DOI
1410
Thin cloud removal
BibRef
Shen, X.L.[Xiao-Le],
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IEEE DOI
1603
Absorption
BibRef
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BibRef
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Modeling of Thin-Cloud TOA Reflectance Using Empirical Relationships
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IEEE DOI
1901
Cloud computing, Remote sensing, Optical sensors,
Artificial satellites, Earth, Clouds, Optical imaging,
observed and modeled top-of-atmosphere (TOA) reflectance from thin clouds
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Xu, M.[Meng],
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Elsevier DOI
1903
Cloud removal,
Noise-adjusted principal components transform (NAPCT),
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Li, W.B.[Wen-Bo],
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Elsevier DOI
1906
Convolutional neural network, Residual blocks,
Symmetrical concatenation, Thin cloud removal
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Guo, Q.,
Hu, H.,
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Haze and Thin Cloud Removal Using Elliptical Boundary Prior for
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GeoRS(57), No. 11, November 2019, pp. 9124-9137.
IEEE DOI
1911
Remote sensing, Sensors, Correlation, Cloud computing, Estimation,
Clouds, Earth, Elliptical boundary, haze thickness prior, visible remote sensing image dehazing
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Li, J.[Jun],
Wu, Z.C.[Zhao-Cong],
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Thin cloud removal in optical remote sensing images based on
generative adversarial networks and physical model of cloud
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PandRS(166), 2020, pp. 373-389.
Elsevier DOI
2007
Cloud removal, Thin clouds, Physical model of cloud distortion,
Generative Adversarial Networks (GANs), Image decomposition
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Wen, X.[Xue],
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Hu, Y.X.[Yu-Xin],
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Generative Adversarial Learning in YUV Color Space for Thin Cloud
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2104
BibRef
Dong, P.Y.[Ping-Yi],
Liu, L.[Lei],
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Application of M5 Model Tree in Passive Remote Sensing of Thin Ice
Cloud Microphysical Properties in Terahertz Region,
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DOI Link
2107
BibRef
Li, J.[Jun],
Wu, Z.C.[Zhao-Cong],
Hu, Z.W.[Zhong-Wen],
Li, Z.L.[Zi-Long],
Wang, Y.S.[Yi-Song],
Molinier, M.[Matthieu],
Deep Learning Based Thin Cloud Removal Fusing Vegetation Red Edge and
Short Wave Infrared Spectral Information for Sentinel-2A Imagery,
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2101
BibRef
Chen, H.[Hui],
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Attentive generative adversarial network for removing thin cloud from
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IET-IPR(15), No. 4, 2021, pp. 856-867.
DOI Link
2106
BibRef
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Lyu, X.R.[Xin-Rong],
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Semi-supervised thin cloud removal with mutually beneficial guides,
PandRS(192), 2022, pp. 327-343.
Elsevier DOI
2209
Thin cloud removal, Semi-supervised learning, Mutually beneficial guides
BibRef
Wu, R.Z.[Ren-Zhe],
Liu, G.X.[Guo-Xiang],
Lv, J.[Jichao],
Fu, Y.[Yin],
Bao, X.[Xin],
Shama, A.[Age],
Cai, J.[Jialun],
Sui, B.[Baikai],
Wang, X.W.[Xiao-Wen],
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An Innovative Approach for Effective Removal of Thin Clouds in
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2305
BibRef
Zi, Y.[Yue],
Ding, H.D.[Hai-Dong],
Xie, F.Y.[Feng-Ying],
Jiang, Z.G.[Zhi-Guo],
Song, X.D.[Xue-Dong],
Wavelet Integrated Convolutional Neural Network for Thin Cloud
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RS(15), No. 3, 2023, pp. xx-yy.
DOI Link
2302
BibRef
Guo, Y.J.[Yu-Jun],
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Zhang, H.Y.[Hong-Yan],
Blind single-image-based thin cloud removal using a cloud perception
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PandRS(206), 2023, pp. 63-86.
Elsevier DOI
2312
Cloud removal, Single-image-based,
Fast Fourier convolution (FFC), Cloud perception, Long-range modeling
BibRef
Tan, Z.C.[Zhan Cong],
Du, X.F.[Xiao Feng],
Man, W.[Wang],
Xie, X.Z.[Xiao Zhu],
Wang, G.S.[Gui Song],
Nie, Q.[Qin],
Unsupervised remote sensing image thin cloud removal method based on
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IET-IPR(18), No. 7, 2024, pp. 1844-1861.
DOI Link
2405
image reconstruction, remote sensing, unsupervised learning
BibRef
Toizumi, T.,
Zini, S.,
Sagi, K.,
Kaneko, E.,
Tsukada, M.,
Schettini, R.,
Artifact-Free Thin Cloud Removal Using Gans,
ICIP19(3596-3600)
IEEE DOI
1910
Remote sensing, Generative adversarial nets,
Multi-spectral image, Cloud removal.
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Liu, X.[Xing],
Jiang, S.M.[Song-Mei],
A new method of information enhancement for hyper-spectrum image
covered with thin clouds and realization based on IDL,
IASP09(5-8).
IEEE DOI
0904
BibRef
Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Cloud Detection, Ground-Based .