19.4.3.3 Super Resolution for Hyperspectral Data

Chapter Contents (Back)
Super Resolution. Hyperspectral. Hyperspectral Super Resolution.
See also Super Resolution for Remote Sensing Applications. Similar to:
See also Pansharpening, Fusion of Aerial Images.

Simoes, M.[Miguel], Bioucas-Dias, J.[Jose], Almeida, L.B.[Luis B.], Chanussot, J.[Jocelyn],
A Convex Formulation for Hyperspectral Image Superresolution via Subspace-Based Regularization,
GeoRS(53), No. 6, June 2015, pp. 3373-3388.
IEEE DOI 1503
BibRef
Earlier:
Hyperspectral image superresolution: An edge-preserving convex formulation,
ICIP14(4166-4170)
IEEE DOI 1502
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
Dictionaries BibRef

Yang, J.[Jing], 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 1702
BibRef

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 BibRef

Kwan, C.[Chiman], Choi, J.H.[Joon Hee], Chan, S.H.[Stanley H.], Zhou, J.[Jin], Budavari, B.[Bence],
A Super-Resolution and Fusion Approach to Enhancing Hyperspectral Images,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
BibRef

Fu, Y.[Ying], Zhang, T.[Tao], Zheng, Y.Q.[Yin-Qiang], Zhang, D.B.[De-Bing], Huang, H.[Hua],
Joint Camera Spectral Response Selection and Hyperspectral Image Recovery,
PAMI(44), No. 1, January 2022, pp. 256-272.
IEEE DOI 2112
BibRef
Earlier:
Joint Camera Spectral Sensitivity Selection and Hyperspectral Image Recovery,
ECCV18(III: 812-828).
Springer DOI 1810
Hyperspectral imaging, Cameras, Training, Spatial resolution, Encoding, Lighting, Pattern analysis, and classification BibRef

Zhang, L.[Lin], Fu, Y.[Ying], Zheng, Y.Q.[Yin-Qiang], Huang, H.[Hua],
Camera spectral sensitivity, illumination and spectral reflectance estimation for a hybrid hyperspectral image capture system,
ICIP17(545-545)
IEEE DOI 1803
cameras, geophysical image processing, hyperspectral imaging, image colour analysis, image reconstruction, spectral reflectance recovery BibRef

Zou, Y.H.[Yun-Hao], Fu, Y.[Ying], Zheng, Y.Q.[Yin-Qiang], Li, W.[Wei],
CSR-Net: Camera Spectral Response Network for Dimensionality Reduction and Classification in Hyperspectral Imagery,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Lin, Y.G.[Yong-Gang], Zheng, Y.R.[Yong-Rong], Fu, Y.[Ying], Huang, H.[Hua],
Hyperspectral image super-resolution under misaligned hybrid camera system,
IET-IPR(12), No. 10, October 2018, pp. 1824-1831.
DOI Link 1809
BibRef

Fu, Y.[Ying], Zheng, Y.Q.[Yin-Qiang], Huang, H.[Hua], Sato, I.[Imari], 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,
RS(12), No. 16, 2020, pp. xx-yy.
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,
IP(25), No. 5, May 2016, pp. 2337-2352.
IEEE DOI 1604
Dictionaries BibRef

Wang, Y.[Yao], Chen, X.[Xi'ai], Han, Z.[Zhi], He, S.Y.[Shi-Ying],
Hyperspectral Image Super-Resolution via Nonlocal Low-Rank Tensor Approximation and Total Variation Regularization,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

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

Han, X.H.[Xian-Hua], 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 in mixed Poisson-Gaussian noise,
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 BibRef

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 spectral unmixing,
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 convolutional networks,
SP:IC(110), 2023, pp. 116884.
Elsevier DOI 2212
BibRef

Mei, S.H.[Shao-Hui], Yuan, X.[Xin], Ji, J.Y.[Jing-Yu], Zhang, Y.F.[Yi-Fan], Wan, S.[Shuai], Du, Q.[Qian],
Hyperspectral Image Spatial Super-Resolution via 3D Full Convolutional Neural Network,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Mei, S.H.[Shao-Hui], Jiang, R.T.[Rui-Tuo], Li, X.[Xu], 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
BibRef

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], Sun, L.[Le],
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], Li, Y.S.[Yun-Song], 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 BibRef

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
BibRef

Wu, R.Y.[Rui-Yuan], Ma, W.K.[Wing-Kin], Fu, X.[Xiao], Li, Q.[Qiang],
Hyperspectral Super-Resolution via Global-Local Low-Rank Matrix Estimation,
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) BibRef

Hu, J.[Jing], Zhao, M.H.[Ming-Hua], Li, Y.S.[Yun-Song],
Hyperspectral Image Super-Resolution by Deep Spatial-Spectral Exploitation,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef
And: Correction: RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Hu, J.[Jing], Li, T.T.[Ting-Ting], Zhao, M.H.[Ming-Hua], Wang, F.[Fei], Ning, J.W.[Jia-Wei],
A Gated Content-Oriented Residual Dense Network for Hyperspectral Image Super-Resolution,
RS(15), No. 13, 2023, pp. 3378.
DOI Link 2307
BibRef

Zhang, X.Y.[Xin-Yi], Dong, H.[Hang], Hu, Z.[Zhe], Lai, W.S.[Wei-Sheng], Wang, F.[Fei], Yang, M.H.[Ming-Hsuan],
Gated Fusion Network for Degraded Image Super Resolution,
IJCV(128), No. 6, June 2020, pp. 1699-1721.
Springer DOI 2006
BibRef

Zhang, C.[Chi], Zhang, M.J.[Ming-Jin], Li, Y.S.[Yun-Song], Gao, X.B.[Xin-Bo], Qiu, S.[Shi],
Difference Curvature Multidimensional Network for Hyperspectral Image Super-Resolution,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Mullah, H.U.[Helal Uddin], Deka, B.[Bhabesh], Prasad, A.V.V.,
Fast multi-spectral image super-resolution via sparse representation,
IET-IPR(14), No. 12, October 2020, pp. 2833-2844.
DOI Link 2010
BibRef

Zhu, Z.Y.[Zhi-Yu], Hou, J.H.[Jun-Hui], Chen, J.[Jie], Zeng, H.Q.[Huan-Qiang], Zhou, J.T.[Jian-Tao],
Hyperspectral Image Super-Resolution via Deep Progressive Zero-Centric Residual Learning,
IP(30), 2021, pp. 1423-1438.
IEEE DOI 2012
Spatial resolution, Image reconstruction, Tensors, Hyperspectral imaging, Residual neural networks, cross-modality BibRef

Wang, X.H.[Xiu-Heng], Chen, J.[Jie], Wei, Q.[Qi], Richard, C.[Cédric],
Hyperspectral Image Super-Resolution via Deep Prior Regularization With Parameter Estimation,
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 BibRef

Lin, Y.X.[Yu-Xin], Ling, B.W.K.[Bingo Wing-Kuen], Hu, L.Y.[Ling-Yue], Zheng, Y.T.[Yi-Ting], Xu, N.[Nuo], Zhou, X.L.[Xue-Ling], Wang, X.P.[Xin-Peng],
Hyperspectral Image Enhancement by Two Dimensional Quaternion Valued Singular Spectrum Analysis for Object Recognition,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Zheng, K., Gao, L., Liao, W., Hong, D., Zhang, B., Cui, X., Chanussot, J.,
Coupled Convolutional Neural Network With Adaptive Response Function Learning for Unsupervised Hyperspectral Super Resolution,
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], Zhang, B.[Bing], Gamba, P.[Paolo], Chanussot, J.[Jocelyn],
Spectral Superresolution of Multispectral Imagery With Joint Sparse and Low-Rank Learning,
GeoRS(59), No. 3, March 2021, pp. 2269-2280.
IEEE DOI 2103
Dictionaries, Image reconstruction, Task analysis, Spatial resolution, Imaging, Dictionary learning, hyperspectral, superresolution BibRef

Dong, W.S.[Wei-Sheng], Zhou, C.[Chen], Wu, F.F.[Fang-Fang], Wu, J.J.[Jin-Jian], Shi, G.M.[Guang-Ming], Li, X.[Xin],
Model-Guided Deep Hyperspectral Image Super-Resolution,
IP(30), 2021, pp. 5754-5768.
IEEE DOI 2106
Iterative algorithms, Computational modeling, Superresolution, Optimization, Linear programming, Inverse problems, deep convolutional network BibRef

Hou, J.H.[Jin-Hui], Zhu, Z.Y.[Zhi-Yu], Hou, J.H.[Jun-Hui], Zeng, H.Q.[Huan-Qiang], Wu, J.J.[Jin-Jian], 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 BibRef

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 BibRef

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
BibRef

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 Learning,
RS(15), No. 11, 2023, pp. 2853.
DOI Link 2306
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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


Zhang, M.J.[Ming-Jin], Zhang, C.[Chi], Zhang, Q.M.[Qi-Ming], Guo, J.[Jie], Gao, X.B.[Xin-Bo], Zhang, J.[Jing],
ESSAformer: Efficient Transformer for Hyperspectral Image Super-resolution,
ICCV23(23016-23027)
IEEE DOI 2401
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 .


Last update:Mar 16, 2024 at 20:36:19