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Bioucas-Dias, J.[Jose],
Almeida, L.B.[Luis B.],
Chanussot, J.[Jocelyn],
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Subspace-Based Regularization,
GeoRS(53), No. 6, June 2015, pp. 3373-3388.
IEEE DOI
1503
BibRef
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Hyperspectral image superresolution:
An edge-preserving convex formulation,
ICIP14(4166-4170)
IEEE DOI
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geophysical image processing.
Data integration
BibRef
Veganzones, M.A.,
Simoes, M.,
Licciardi, G.,
Yokoya, N.,
Bioucas-Dias, J.M.,
Chanussot, J.,
Hyperspectral Super-Resolution of Locally Low Rank Images From
Complementary Multisource Data,
IP(25), No. 1, January 2016, pp. 274-288.
IEEE DOI
1601
BibRef
Earlier: A1, A2, A3, A5, A6, Only:
ICIP14(703-707)
IEEE DOI
1502
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BibRef
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Li, Y.[Ying],
Chan, J.C.W.[Jonathan Cheung-Wai],
Shen, Q.A.[Qi-Ang],
Image Fusion for Spatial Enhancement of Hyperspectral Image via Pixel
Group Based Non-Local Sparse Representation,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link
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Yi, C.,
Zhao, Y.Q.,
Chan, J.C.W.,
Hyperspectral Image Super-Resolution Based on Spatial and Spectral
Correlation Fusion,
GeoRS(56), No. 7, July 2018, pp. 4165-4177.
IEEE DOI
1807
geophysical image processing, image fusion, image reconstruction,
image representation, image resolution, HS patch matrix,
super-resolution enhancement
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Kwan, C.[Chiman],
Choi, J.H.[Joon Hee],
Chan, S.H.[Stanley H.],
Zhou, J.[Jin],
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PAMI(44), No. 1, January 2022, pp. 256-272.
IEEE DOI
2112
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Joint Camera Spectral Sensitivity Selection and Hyperspectral Image
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Springer DOI
1810
Hyperspectral imaging, Cameras, Training, Spatial resolution,
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ICIP17(545-545)
IEEE DOI
1803
cameras, geophysical image processing, hyperspectral imaging,
image colour analysis, image reconstruction, spectral reflectance recovery
BibRef
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Fu, Y.[Ying],
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RS(12), No. 20, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Lin, Y.G.[Yong-Gang],
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Hyperspectral image super-resolution under misaligned hybrid camera
system,
IET-IPR(12), No. 10, October 2018, pp. 1824-1831.
DOI Link
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Fu, Y.[Ying],
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Sato, Y.I.[Yo-Ichi],
Hyperspectral Image Super-Resolution With a Mosaic RGB Image,
IP(27), No. 11, November 2018, pp. 5539-5552.
IEEE DOI
1809
cameras, geophysical image processing, hyperspectral imaging,
image colour analysis, image resolution, image segmentation,
non-local low-rank approximation
BibRef
Fu, Y.[Ying],
Zhang, T.[Tao],
Zheng, Y.Q.[Yin-Qiang],
Zhang, D.B.[De-Bing],
Huang, H.[Hua],
Hyperspectral Image Super-Resolution With Optimized RGB Guidance,
CVPR19(11653-11662).
IEEE DOI
2002
BibRef
Xu, Y.[Yang],
Wu, Z.B.[Ze-Bin],
Chanussot, J.[Jocelyn],
Wei, Z.H.[Zhi-Hui],
Nonlocal Patch Tensor Sparse Representation for Hyperspectral Image
Super-Resolution,
IP(28), No. 6, June 2019, pp. 3034-3047.
IEEE DOI
1905
geophysical image processing, hyperspectral imaging,
image coding, image denoising, image reconstruction,
nonlocal patch tensor
BibRef
Ye, F.[Fei],
Wu, Z.B.[Ze-Bin],
Jia, X.P.[Xiu-Ping],
Chanussot, J.[Jocelyn],
Xu, Y.[Yang],
Wei, Z.H.[Zhi-Hui],
Bayesian Nonlocal Patch Tensor Factorization for Hyperspectral Image
Super-Resolution,
IP(32), 2023, pp. 5877-5892.
IEEE DOI
2311
BibRef
Ren, X.X.[Xiao-Xu],
Lu, L.F.[Liang-Fu],
Chanussot, J.[Jocelyn],
Toward Super-Resolution Image Construction Based on Joint Tensor
Decomposition,
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DOI Link
2008
BibRef
Dong, W.S.[Wei-Sheng],
Fu, F.Z.[Fa-Zuo],
Shi, G.M.[Guang-Ming],
Cao, X.[Xun],
Wu, J.J.[Jin-Jian],
Li, G.Y.[Guang-Yu],
Li, X.[Xin],
Hyperspectral Image Super-Resolution via Non-Negative Structured
Sparse Representation,
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1604
Dictionaries
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Hyperspectral Image Super-Resolution via Nonlocal Low-Rank Tensor
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RS(9), No. 12, 2017, pp. xx-yy.
DOI Link
1802
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Irmak, H.,
Akar, G.B.,
Yuksel, S.E.,
A MAP-Based Approach for Hyperspectral Imagery Super-Resolution,
IP(27), No. 6, June 2018, pp. 2942-2951.
IEEE DOI
1804
Bayes methods, Dictionaries, Hyperspectral imaging,
Image reconstruction, Minimization, Spatial resolution,
super-resolution reconstruction
BibRef
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Shi, B.X.[Bo-Xin],
Zheng, Y.Q.[Yin-Qiang],
Self-Similarity Constrained Sparse Representation for Hyperspectral
Image Super-Resolution,
IP(27), No. 11, November 2018, pp. 5625-5637.
IEEE DOI
1809
BibRef
And:
SSF-CNN: Spatial and Spectral Fusion with CNN for Hyperspectral Image
Super-Resolution,
ICIP18(2506-2510)
IEEE DOI
1809
hyperspectral imaging, image coding, image fusion,
image reconstruction, image representation, image resolution,
non-negative sparse coding.
Spatial resolution, Databases, Feature extraction, SSF-CNN
BibRef
Zhang, L.,
Wei, W.,
Bai, C.,
Gao, Y.,
Zhang, Y.,
Exploiting Clustering Manifold Structure for Hyperspectral Imagery
Super-Resolution,
IP(27), No. 12, December 2018, pp. 5969-5982.
IEEE DOI
1810
hyperspectral imaging, image reconstruction, image resolution,
learning (artificial intelligence), optimisation,
HSI super-resolution
BibRef
Gao, D.S.[Dong-Sheng],
Hu, Z.T.[Zhen-Tao],
Ye, R.Z.[Ren-Zhen],
Self-Dictionary Regression for Hyperspectral Image Super-Resolution,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link
1811
BibRef
He, Z.[Zhi],
Liu, L.[Lin],
Hyperspectral Image Super-Resolution Inspired by Deep Laplacian
Pyramid Network,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Zou, C.Z.[Chang-Zhong],
Xia, Y.S.[You-Shen],
Bayesian dictionary learning for hyperspectral image super resolution
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SP:IC(60), No. 1, 2018, pp. 29-41.
Elsevier DOI
1712
BibRef
And:
Blind hyperspectral image super resolution via simultaneously sparse
and TV constraint,
ICIP17(4048-4052)
IEEE DOI
1803
Estimation error, Hyperspectral imaging, Kernel, Optimization,
Spatial resolution, blind super resolution, hyperspectral image,
total variation.
BibRef
Huang, L.Q.[Li-Qing],
Xia, Y.S.[You-Shen],
Fast Blind Image Super Resolution Using Matrix-Variable Optimization,
CirSysVideo(31), No. 3, March 2021, pp. 945-955.
IEEE DOI
2103
Image resolution, Kernel, Image reconstruction,
Matrix decomposition, Sparse matrices, Optimization methods,
reconstruction quality
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Huang, L.Q.[Li-Qing],
Xia, Y.S.[You-Shen],
Ye, T.T.[Tian-Tian],
Effective Blind Image Deblurring Using Matrix-Variable Optimization,
IP(30), 2021, pp. 4653-4666.
IEEE DOI
2105
BibRef
Zou, C.Z.[Chang-Zhong],
Huang, X.S.[Xu-Sheng],
Hyperspectral image super-resolution combining with deep learning and
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SP:IC(84), 2020, pp. 115833.
Elsevier DOI
2004
Hyperspectral image (HSI), Super-resolution,
Deep residual convolutional neural network (DRCNN),
Total variation (TV) regularity
BibRef
Zou, C.Z.[Chang-Zhong],
Zhang, C.[Can],
Hyperspectral image super-resolution using cluster-based deep
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SP:IC(110), 2023, pp. 116884.
Elsevier DOI
2212
BibRef
Mei, S.H.[Shao-Hui],
Yuan, X.[Xin],
Ji, J.Y.[Jing-Yu],
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Wan, S.[Shuai],
Du, Q.[Qian],
Hyperspectral Image Spatial Super-Resolution via 3D Full
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RS(9), No. 11, 2017, pp. xx-yy.
DOI Link
1712
BibRef
Mei, S.H.[Shao-Hui],
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Du, Q.[Qian],
Spatial and Spectral Joint Super-Resolution Using Convolutional
Neural Network,
GeoRS(58), No. 7, July 2020, pp. 4590-4603.
IEEE DOI
2006
Spatial resolution, Image reconstruction, Hyperspectral imaging,
Signal resolution, Convolutional neural network (CNN),
super-resolution (SR)
BibRef
Mei, S.H.[Shao-Hui],
Yuan, X.[Xin],
Ji, J.Y.[Jing-Yu],
Wan, S.[Shuai],
Hou, J.,
Du, Q.[Qian],
Hyperspectral Image Super-Resolution Via Convolutional Neural Network,
ICIP17(4297-4301)
IEEE DOI
1803
Distortion, Hyperspectral imaging, Image reconstruction,
Image restoration, Spatial resolution, Hyperspectral,
super-resolution
BibRef
Mei, S.H.[Shao-Hui],
Chen, X.F.[Xiao-Feng],
Zhang, Y.F.[Yi-Fan],
Li, J.[Jun],
Plaza, A.[Antonio],
Accelerating Convolutional Neural Network-Based Hyperspectral Image
Classification by Step Activation Quantization,
GeoRS(60), 2022, pp. 1-12.
IEEE DOI
2112
Quantization (signal), Convolution, Feature extraction,
Acceleration, Hyperspectral imaging, Training, Memory management,
weight quantification
BibRef
Gao, H.M.[Hong-Min],
Wu, H.Y.[Hong-Yi],
Chen, Z.H.[Zhong-Hao],
Zhang, Y.F.[Yun-Fei],
Zhang, Y.Y.[Yi-Yan],
Li, C.M.[Chen-Ming],
Multiscale Spectral-Spatial Cross-Extraction Network for
Hyperspectral Image Classification,
IET-IPR(16), No. 3, 2022, pp. 755-771.
DOI Link
2202
BibRef
Du, T.W.[Tian-Wen],
Zhang, Y.F.[Yi-Feng],
Single Image Super-Resolution Algorithm Based on Enhanced Generative
Adversarial Network,
ICIVC21(357-361)
IEEE DOI
2112
PSNR, Image color analysis, Superresolution,
Benchmark testing, Generative adversarial networks,
loss function
BibRef
Wang, B.R.[Bao-Rui],
Zhang, Y.F.[Yi-Fan],
Feng, Y.[Yan],
Xie, B.[Bobo],
Mei, S.H.[Shao-Hui],
Attention-Enhanced Generative Adversarial Network for Hyperspectral
Imagery Spatial Super-Resolution,
RS(15), No. 14, 2023, pp. 3644.
DOI Link
2307
BibRef
Li, J.J.[Jiao-Jiao],
Cui, R.X.[Ru-Xing],
Li, B.[Bo],
Song, R.[Rui],
Li, Y.S.[Yun-Song],
Du, Q.[Qian],
Hyperspectral Image Super-Resolution with 1D-2D Attentional
Convolutional Neural Network,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link
1912
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Xu, H.[Hao],
Yao, W.[Wei],
Cheng, L.[Li],
Li, B.[Bo],
Multiple Spectral Resolution 3D Convolutional Neural Network for
Hyperspectral Image Classification,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Li, J.J.[Jiao-Jiao],
Wu, C.X.[Chao-Xiong],
Song, R.[Rui],
Xie, W.Y.[Wei-Ying],
Ge, C.R.[Chi-Ru],
Li, B.[Bo],
Li, Y.S.[Yun-Song],
Hybrid 2-D-3-D Deep Residual Attentional Network With Structure
Tensor Constraints for Spectral Super-Resolution of RGB Images,
GeoRS(59), No. 3, March 2021, pp. 2321-2335.
IEEE DOI
2103
Hyperspectral imaging, Image reconstruction, Feature extraction,
Spatial resolution, Tensors, Correlation, Attention mechanism,
structure tensor
BibRef
Jiang, R.T.[Rui-Tuo],
Li, X.[Xu],
Mei, S.H.[Shao-Hui],
Li, L.X.[Li-Xin],
Yue, S.G.[Shi-Gang],
Zhang, L.[Lei],
Learning Spatial and Spectral Features via 2D-1D Generative
Adversarial Network for Hyperspectral Image Super-Resolution,
ICIP19(2149-2153)
IEEE DOI
1910
Hyperspectral images, super-resolution, generative adversarial network
BibRef
Tang, S.Z.[Song-Ze],
Xu, Y.[Yang],
Huang, L.[Lili],
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Hyperspectral Image Super-Resolution via Adaptive Dictionary Learning
and Double L_1 Constraint,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Xie, W.Y.[Wei-Ying],
Shi, Y.Z.[Yan-Zi],
Li, Y.S.[Yun-Song],
Jia, X.P.[Xiu-Ping],
Lei, J.[Jie],
High-quality spectral-spatial reconstruction using saliency detection
and deep feature enhancement,
PR(88), 2019, pp. 139-152.
Elsevier DOI
1901
Hyperspectral image, Quality enhancement, Structure tensor,
Deep neural networks, Adaptive weighting, Nonnegative matrix factorization
BibRef
Li, X.Y.[Xiao-Yan],
Zhang, L.[Lefei],
You, J.[Jane],
Domain Transfer Learning for Hyperspectral Image Super-Resolution,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Dhason, H.G.C.A.[Heltin Genitha Cyril Amala],
Muthaia, I.[Indhumathi],
Sakthivel, S.P.[Shanmuga Priyaa],
Shanmugam, S.[Sanjeevi],
Super-resolution mapping of hyperspectral satellite images using hybrid
genetic algorithm,
IET-IPR(14), No. 7, 29 May 2020, pp. 1281-1290.
DOI Link
2005
BibRef
Li, J.J.[Jiao-Jiao],
Cui, R.X.[Ru-Xing],
Li, B.[Bo],
Song, R.[Rui],
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Dai, Y.C.[Yu-Chao],
Du, Q.[Qian],
Hyperspectral Image Super-Resolution by Band Attention Through
Adversarial Learning,
GeoRS(58), No. 6, June 2020, pp. 4304-4318.
IEEE DOI
2005
Adversarial learning, band attention,
hyperspectral image (HSI) super-resolution (SR)
BibRef
Arun, P.V.,
Buddhiraju, K.M.,
Porwal, A.,
Chanussot, J.,
CNN-Based Super-Resolution of Hyperspectral Images,
GeoRS(58), No. 9, September 2020, pp. 6106-6121.
IEEE DOI
2008
Spatial resolution, Hyperspectral imaging, Image reconstruction,
Dictionaries, Convolutional codes,
super-resolution
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Sun, L.[Le],
He, C.X.[Cheng-Xun],
Zheng, Y.H.[Yu-Hui],
Tang, S.Z.[Song-Ze],
SLRL4D: Joint Restoration of Subspace Low-Rank Learning and Non-Local
4-D Transform Filtering for Hyperspectral Image,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
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Wu, R.Y.[Rui-Yuan],
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Hyperspectral Super-Resolution via Global-Local Low-Rank Matrix
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GeoRS(58), No. 10, October 2020, pp. 7125-7140.
IEEE DOI
2009
Spatial resolution, Estimation, Sensors, Dictionaries,
Hyperspectral imaging, Optimization, Endmember variability (EV),
low-rank matrix estimation
BibRef
Kanatsoulis, C.I.[Charilaos I.],
Fu, X.[Xiao],
Sidiropoulos, N.D.[Nicholas D.],
Ma, W.K.[Wing-Kin],
Hyperspectral Super-Resolution:
Combining Low Rank Tensor and Matrix Structure,
ICIP18(3318-3322)
IEEE DOI
1809
Tensile stress, Spatial resolution, Hyperspectral imaging,
Degradation, Signal resolution, Hyperspectral imaging, matrix factorization
BibRef
Hu, J.[Jing],
Jia, X.P.[Xiu-Ping],
Li, Y.S.[Yun-Song],
He, G.[Gang],
Zhao, M.H.[Ming-Hua],
Hyperspectral Image Super-Resolution via Intrafusion Network,
GeoRS(58), No. 10, October 2020, pp. 7459-7471.
IEEE DOI
2009
Spatial resolution, Convolution, Image reconstruction,
Hyperspectral imaging, Convolutional neural networks,
super-resolution (SR)
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Hu, J.[Jing],
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Li, Y.S.[Yun-Song],
Hyperspectral Image Super-Resolution by Deep Spatial-Spectral
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RS(11), No. 10, 2019, pp. xx-yy.
DOI Link
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RS(11), No. 24, 2019, pp. xx-yy.
DOI Link
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Gated Fusion Network for Degraded Image Super Resolution,
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Springer DOI
2006
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Zhang, C.[Chi],
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Difference Curvature Multidimensional Network for Hyperspectral Image
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RS(13), No. 17, 2021, pp. xx-yy.
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Mullah, H.U.[Helal Uddin],
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Zhu, Z.Y.[Zhi-Yu],
Hou, J.H.[Jun-Hui],
Chen, J.[Jie],
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Hyperspectral Image Super-Resolution via Deep Progressive
Zero-Centric Residual Learning,
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IEEE DOI
2012
Spatial resolution, Image reconstruction, Tensors,
Hyperspectral imaging, Residual neural networks,
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Wang, X.H.[Xiu-Heng],
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Richard, C.[Cédric],
Hyperspectral Image Super-Resolution via Deep Prior Regularization
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CirSysVideo(32), No. 4, April 2022, pp. 1708-1723.
IEEE DOI
2204
Superresolution, Hyperspectral imaging, Optimization, Tensors,
Spatial resolution, Degradation, Matrix decomposition,
regularization parameter estimation
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Lin, Y.X.[Yu-Xin],
Ling, B.W.K.[Bingo Wing-Kuen],
Hu, L.Y.[Ling-Yue],
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Xu, N.[Nuo],
Zhou, X.L.[Xue-Ling],
Wang, X.P.[Xin-Peng],
Hyperspectral Image Enhancement by Two Dimensional Quaternion Valued
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DOI Link
2102
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Zheng, K.,
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GeoRS(59), No. 3, March 2021, pp. 2487-2502.
IEEE DOI
2103
Spatial resolution, Hyperspectral imaging, Geoscience, Training,
Adaptive learning, autoencoder,
super-resolution
BibRef
Gao, L.R.[Lian-Ru],
Hong, D.F.[Dan-Feng],
Yao, J.[Jing],
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Spectral Superresolution of Multispectral Imagery With Joint Sparse
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IEEE DOI
2103
Dictionaries, Image reconstruction, Task analysis,
Spatial resolution, Imaging, Dictionary learning, hyperspectral,
superresolution
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Dong, W.S.[Wei-Sheng],
Zhou, C.[Chen],
Wu, F.F.[Fang-Fang],
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IP(30), 2021, pp. 5754-5768.
IEEE DOI
2106
Iterative algorithms, Computational modeling, Superresolution,
Optimization, Linear programming, Inverse problems,
deep convolutional network
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Hou, J.H.[Jin-Hui],
Zhu, Z.Y.[Zhi-Yu],
Hou, J.H.[Jun-Hui],
Zeng, H.Q.[Huan-Qiang],
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Zhou, J.T.[Jian-Tao],
Deep Posterior Distribution-Based Embedding for Hyperspectral Image
Super-Resolution,
IP(31), 2022, pp. 5720-5732.
IEEE DOI
2209
Superresolution, Feature extraction, Image reconstruction,
Convolution, Spatial resolution, Iterative methods, probability
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Lu, X.C.[Xiao-Chen],
Zhang, J.P.[Jun-Ping],
Yang, D.Z.[De-Zheng],
Xu, L.T.[Long-Ting],
Jia, F.D.[Feng-De],
Cascaded Convolutional Neural Network-Based Hyperspectral Image
Resolution Enhancement via an Auxiliary Panchromatic Image,
IP(30), 2021, pp. 6815-6828.
IEEE DOI
2108
Spatial resolution, Image resolution, Image fusion, Sensors,
Hyperspectral imaging, Earth, Mixture models,
pan-sharpening
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Lu, X.C.[Xiao-Chen],
Li, T.[Tong],
Zhang, J.P.[Jun-Ping],
Jia, F.D.[Feng-De],
A Novel Unmixing-Based Hypersharpening Method via Convolutional
Neural Network,
GeoRS(60), 2022, pp. 1-14.
IEEE DOI
2112
Spatial resolution, Image fusion, Tensors, Mixture models,
Task analysis, Image reconstruction, Collaboration,
multispectral (MS)
BibRef
Lu, X.C.[Xiao-Chen],
Yang, D.Z.[De-Zheng],
Zhang, J.P.[Jun-Ping],
Jia, F.D.[Feng-De],
Hyperspectral Image Super-Resolution Based on Spatial
Correlation-Regularized Unmixing Convolutional Neural Network,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link
2110
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Zhang, S.L.[Shao-Lei],
Fu, G.Y.[Guang-Yuan],
Wang, H.Q.[Hong-Qiao],
Zhao, Y.Q.[Yu-Qing],
Spectral recovery-guided hyperspectral super-resolution using
transfer learning,
IET-IPR(15), No. 11, 2021, pp. 2656-2665.
DOI Link
2108
BibRef
Hang, R.L.[Ren-Long],
Liu, Q.S.[Qing-Shan],
Li, Z.[Zhu],
Spectral Super-Resolution Network Guided by Intrinsic Properties of
Hyperspectral Imagery,
IP(30), 2021, pp. 7256-7265.
IEEE DOI
2108
Superresolution, Image reconstruction, Correlation,
Hyperspectral imaging, Deep learning, Spatial resolution,
self-supervised subnetwork
BibRef
Liu, D.H.[Deng-Hong],
Li, J.[Jie],
Yuan, Q.Q.[Qiang-Qiang],
A Spectral Grouping and Attention-Driven Residual Dense Network for
Hyperspectral Image Super-Resolution,
GeoRS(59), No. 9, September 2021, pp. 7711-7725.
IEEE DOI
2109
Feature extraction, Correlation, Image reconstruction,
Spatial resolution, Superresolution, Hyperspectral imaging,
super-resolution (SR)
BibRef
He, W.[Wei],
Chen, Y.[Yong],
Yokoya, N.[Naoto],
Li, C.[Chao],
Zhao, Q.B.[Qi-Bin],
Hyperspectral super-resolution via coupled tensor ring factorization,
PR(122), 2022, pp. 108280.
Elsevier DOI
2112
Coupled tensor ring decomposition, Super-resolution,
Hyperspectral, Multispectral
BibRef
Li, Y.D.[Ya-Dong],
Du, Z.H.[Zhen-Hong],
Wu, S.S.[Sen-Sen],
Wang, Y.Y.[Yuan-Yuan],
Wang, Z.Y.[Zhong-Yi],
Zhao, X.W.[Xian-Wei],
Zhang, F.[Feng],
Progressive split-merge super resolution for hyperspectral imagery
with group attention and gradient guidance,
PandRS(182), 2021, pp. 14-36.
Elsevier DOI
2112
Hyperspectral image, Super resolution,
Convolutional neural network, Gradient reconstruction, Group attention module
BibRef
Wei, W.[Wei],
Nie, J.T.[Jiang-Tao],
Zhang, L.[Lei],
Zhang, Y.N.[Yan-Ning],
Unsupervised Recurrent Hyperspectral Imagery Super-Resolution Using
Pixel-Aware Refinement,
GeoRS(60), 2022, pp. 1-15.
IEEE DOI
2112
Image reconstruction, Spatial resolution, Optimization,
Computer science, Training, Spectral analysis, Sparse matrices,
unsupervised deep learning
BibRef
Zhang, L.[Lei],
Nie, J.T.[Jiang-Tao],
Wei, W.[Wei],
Zhang, Y.N.[Yan-Ning],
Liao, S.C.[Sheng-Cai],
Shao, L.[Ling],
Unsupervised Adaptation Learning for Hyperspectral Imagery
Super-Resolution,
CVPR20(3070-3079)
IEEE DOI
2008
Image resolution, Adaptation models, Kernel, Estimation,
Image reconstruction, Unsupervised learning, Hyperspectral imaging
BibRef
Wang, X.Y.[Xin-Ya],
Ma, J.Y.[Jia-Yi],
Jiang, J.J.[Jun-Jun],
Hyperspectral Image Super-Resolution via Recurrent Feedback Embedding
and Spatial-Spectral Consistency Regularization,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI
2112
Hyperspectral imaging, Spatial resolution, Image reconstruction,
Correlation, Feature extraction, Superresolution, Training,
super-resolution (SR)
BibRef
Tang, Z.J.[Zhen-Jie],
Xu, Q.[Qing],
Wu, P.F.[Peng-Fei],
Shi, Z.W.[Zhen-Wei],
Pan, B.[Bin],
Feedback Refined Local-Global Network for Super-Resolution of
Hyperspectral Imagery,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Sun, L.[Le],
Cheng, Q.H.[Qi-Hao],
Chen, Z.G.[Zhi-Guo],
Hyperspectral Image Super-Resolution Method Based on Spectral
Smoothing Prior and Tensor Tubal Row-Sparse Representation,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Wang, X.[Xi],
Xu, T.F.[Ting-Fa],
Zhang, Y.H.[Yu-Han],
Fan, A.[Axin],
Xu, C.[Chang],
Li, J.A.[Jian-An],
Backtracking Reconstruction Network for Three-Dimensional Compressed
Hyperspectral Imaging,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Sun, M.B.[Ming-Bo],
Chen, S.[Shengbo],
Deep Learning-Based Super-Resolution Reconstruction and Algorithm
Acceleration of Mars Hyperspectral CRISM Data,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Zhang, X.T.[Xin-Tong],
Zhang, A.[Aiwu],
Portelli, R.[Raechel],
Zhang, X.[Xizhen],
Guan, H.L.[Hong-Liang],
ZY-1 02D Hyperspectral Imagery Super-Resolution via Endmember Matrix
Constraint Unmixing,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Liu, H.Y.[Hong-Yi],
Jiang, W.[Wen],
Zha, Y.C.[Yu-Chen],
Wei, Z.H.[Zhi-Hui],
Coupled Tensor Block Term Decomposition with Superpixel-Based Graph
Laplacian Regularization for Hyperspectral Super-Resolution,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Li, Q.[Qiang],
Yuan, Y.[Yuan],
Jia, X.P.[Xiu-Ping],
Wang, Q.[Qi],
Dual-Stage Approach Toward Hyperspectral Image Super-Resolution,
IP(31), 2022, pp. 7252-7263.
IEEE DOI
2212
Hyperspectral imaging, Convolution, Spatial resolution,
Superresolution, Image reconstruction, back-projection
BibRef
Wang, H.[Heng],
Wang, C.[Cong],
Yuan, Y.[Yuan],
Asymmetric Dual-Direction Quasi-Recursive Network for Single
Hyperspectral Image Super-Resolution,
CirSysVideo(33), No. 11, November 2023, pp. 6331-6346.
IEEE DOI
2311
BibRef
Xing, C.D.[Chang-Da],
Wang, M.L.[Mei-Ling],
Cong, Y.H.[Yu-Hua],
Wang, Z.S.[Zhi-Sheng],
Duan, C.W.[Chao-Wei],
Liu, Y.[Yiliu],
Sparse coding with morphology segmentation and multi-label fusion for
hyperspectral image super-resolution,
CVIU(227), 2023, pp. 103603.
Elsevier DOI
2301
Hyperspectral image super-resolution, Sparse coding,
Morphology segmentation, Multi-label fusion
BibRef
Zhang, J.[Jing],
Zheng, R.J.[Ren-Jie],
Chen, X.[Xu],
Hong, Z.L.[Zhao-Long],
Li, Y.S.[Yun-Song],
Lu, R.T.[Rui-Tao],
Spectral Correlation and Spatial High-Low Frequency Information of
Hyperspectral Image Super-Resolution Network,
RS(15), No. 9, 2023, pp. xx-yy.
DOI Link
2305
BibRef
Liu, Z.Q.[Zi-Qian],
Wang, W.B.[Wen-Bing],
Ma, Q.[Qing],
Liu, X.M.[Xian-Ming],
Jiang, J.J.[Jun-Jun],
Rethinking 3D-CNN in Hyperspectral Image Super-Resolution,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link
2306
BibRef
Chen, C.[Chi],
Wang, Y.C.[Yong-Cheng],
Zhang, N.[Ning],
Zhang, Y.X.[Yu-Xi],
Zhao, Z.K.[Zhi-Kang],
A Review of Hyperspectral Image Super-Resolution Based on Deep
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RS(15), No. 11, 2023, pp. 2853.
DOI Link
2306
BibRef
Dong, W.Q.[Wen-Qian],
Qu, J.[Jiahui],
Xiao, S.[Song],
Zhang, T.Z.[Tong-Zhen],
Li, Y.S.[Yun-Song],
Jia, X.P.[Xiu-Ping],
Noise Prior Knowledge Informed Bayesian Inference Network for
Hyperspectral Super-Resolution,
IP(32), 2023, pp. 3121-3135.
IEEE DOI
2306
Bayes methods, Spatial resolution, Deep learning, Superresolution,
Mathematical models, Linear programming, Gaussian noise, interpretable
BibRef
Yao, Y.Z.[Yun-Ze],
Hu, J.W.[Jian-Wen],
Liu, Y.T.[Yao-Ting],
Zhao, Y.S.[Yu-Shan],
Spectral-Spatial MLP Network for Hyperspectral Image Super-Resolution,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link
2307
BibRef
Bu, L.J.[Li-Jing],
Dai, D.[Dong],
Zhang, Z.P.[Zheng-Peng],
Yang, Y.[Yin],
Deng, M.J.[Ming-Jun],
Hyperspectral Super-Resolution Reconstruction Network Based on Hybrid
Convolution and Spectral Symmetry Preservation,
RS(15), No. 13, 2023, pp. 3225.
DOI Link
2307
BibRef
Wang, S.[Sai],
Fan, F.L.[Feng-Lei],
Thangka Hyperspectral Image Super-Resolution Based on a
Spatial-Spectral Integration Network,
RS(15), No. 14, 2023, pp. 3603.
DOI Link
2307
BibRef
Sun, S.[Shasha],
Bao, W.X.[Wen-Xing],
Qu, K.[Kewen],
Feng, W.[Wei],
Zhang, X.W.[Xiao-Wu],
Ma, X.[Xuan],
Hyperspectral Image Super-Resolution Algorithm Based on Graph Regular
Tensor Ring Decomposition,
RS(15), No. 20, 2023, pp. 4983.
DOI Link
2310
BibRef
Fang, Y.[Yuan],
Liu, Y.P.[Yi-Peng],
Chi, C.Y.[Chong-Yung],
Long, Z.[Zhen],
Zhu, C.[Ce],
CS2DIPs: Unsupervised HSI Super-Resolution Using Coupled Spatial and
Spectral DIPs,
IP(33), 2024, pp. 3090-3101.
IEEE DOI
2405
Tensors, Electronics packaging, Superresolution,
Spatial resolution, Matrix decomposition, Image restoration,
nonnegative matrix-vector tensor factorization
BibRef
Wang, H.Q.[Hao-Qian],
Zhang, Q.[Qi],
Peng, T.[Tao],
Xu, Z.J.[Zhong-Jie],
Cheng, X.[Xiangai],
Xing, Z.Y.[Zhong-Yang],
Li, T.[Teng],
SSAformer: Spatial-Spectral Aggregation Transformer for Hyperspectral
Image Super-Resolution,
RS(16), No. 10, 2024, pp. 1766.
DOI Link
2405
BibRef
Liao, X.M.[Xiao-Mei],
He, L.R.[Li-Rong],
Mao, J.[Jiayou],
Xu, M.[Meng],
Spectral Superresolution Using Transformer with Convolutional
Spectral Self-Attention,
RS(16), No. 10, 2024, pp. 1688.
DOI Link
2405
BibRef
Zhang, L.[Lei],
Nie, J.T.[Jiang-Tao],
Wei, W.[Wei],
Zhang, Y.N.[Yan-Ning],
Unsupervised Test-Time Adaptation Learning for Effective
Hyperspectral Image Super-Resolution With Unknown Degeneration,
PAMI(46), No. 7, July 2024, pp. 5008-5025.
IEEE DOI
2406
Task analysis, Adaptation models, Superresolution, Data models,
Sensors, Optimization, Knowledge engineering,
unsupervised test-time adaptation learning
BibRef
Ran, R.[Ran],
Deng, L.J.[Liang-Jian],
Zhang, T.J.[Tian-Jing],
Chang, J.L.[Jian-Long],
Wu, X.[Xiao],
Tian, Q.[Qi],
KNLConv: Kernel-Space Non-Local Convolution for Hyperspectral Image
Super-Resolution,
MultMed(26), 2024, pp. 8836-8848.
IEEE DOI
2408
Kernel, Convolution, Feature extraction, Hyperspectral imaging,
Standards, Superresolution, Correlation, superresolution
BibRef
Wu, C.Y.[Chan-Yue],
Wang, D.[Dong],
Bai, Y.P.[Yun-Peng],
Mao, H.Y.[Han-Yu],
Li, Y.[Ying],
Shen, Q.[Qiang],
HSR-Diff: Hyperspectral Image Super-Resolution via Conditional
Diffusion Models,
ICCV23(7060-7070)
IEEE DOI
2401
BibRef
Hussain, S.[Sadia],
Lall, B.[Brejesh],
Spectral Grouping Driven Hyperspectral Super-Resolution,
ICIP23(3210-3214)
IEEE DOI
2312
BibRef
Zhang, Z.Y.[Zhong-Yang],
Xu, Z.Y.[Zhi-Yang],
Ahmed, Z.[Zia],
Salekin, A.[Asif],
Rahman, T.[Tauhidur],
Hyperspectral Image Super-Resolution in Arbitrary Input-Output Band
Settings,
ComputationalApp22(749-759)
IEEE DOI
2202
Adaptation models, Conferences,
Computational modeling, Superresolution, Cameras, Robustness
BibRef
Chang, Y.[Yuan],
Bailey, D.[Donald],
Le Moan, S.[Steven],
A new coefficient estimation method when using PCA for spectral
super-resolution,
IVCNZ21(1-6)
IEEE DOI
2201
Reflectivity, Costs, Dictionaries, Superresolution, Estimation,
Machine learning, Spatial resolution, spectral super-resolution,
dictionary learning
BibRef
Han, X.,
Zheng, Y.,
Chen, Y.,
Multi-Level and Multi-Scale Spatial and Spectral Fusion CNN for
Hyperspectral Image Super-Resolution,
PBDL19(4330-4339)
IEEE DOI
2004
cameras, convolutional neural nets,
hyperspectral imaging, image colour analysis, image fusion, CNN
BibRef
Qu, Y.,
Qi, H.,
Kwan, C.,
Unsupervised Sparse Dirichlet-Net for Hyperspectral Image
Super-Resolution,
CVPR18(2511-2520)
IEEE DOI
1812
Spatial resolution, Decoding, Hyperspectral imaging, Distortion, Sensors
BibRef
Lahoud, F.[Fayez],
Zhou, R.[Ruofan],
Süsstrunk, S.[Sabine],
Multi-modal Spectral Image Super-Resolution,
PerceptualRest18(V:35-50).
Springer DOI
1905
BibRef
Han, X.L.[Xiao-Lin],
Yu, J.[Jing],
Sun, W.D.[Wei-Dong],
Hyperspectral image super-resolution based on non-factorization
sparse representation and dictionary learning,
ICIP17(963-966)
IEEE DOI
1803
Dictionaries, Hyperspectral imaging, Signal resolution,
Sparse matrices, Spatial resolution, dictionary learning,
super-resolution
BibRef
Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Super Resolution for Light Field Images and Data .