12.1.4.8.1 Fusion of Hyperspectral Images

Chapter Contents (Back)
Sensor Fusion. Hyperspectral.

Wilson, T.A., Rogers, S.K., Kabrisky, M.,
Perceptual-Based Image Fusion for Hyperspectral Data,
GeoRS(35), No. 4, July 1997, pp. 1007-1017.
IEEE Top Reference. 9708
BibRef

Chen, C.M., Hepner, G.F., Forster, R.R.,
Fusion of hyperspectral and radar data using the IHS transformation to enhance urban surface features,
PandRS(58), No. 1, June 2003, pp. 19-30.
Elsevier DOI 0307
BibRef

Hardie, R.C., Eismann, M.T., Wilson, G.L.,
MAP Estimation for Hyperspectral Image Resolution Enhancement Using an Auxiliary Sensor,
IP(13), No. 9, September 2004, pp. 1174-1184.
IEEE DOI 0409
BibRef

Eismann, M.T., Hardie, R.C.,
Hyperspectral Resolution Enhancement Using High-Resolution Multispectral Imagery With Arbitrary Response Functions,
GeoRS(43), No. 3, March 2005, pp. 455-465.
IEEE Abstract. 0501
BibRef

Jimenez, L.O., Rivera-Medina, J.L., Rodriguez-Diaz, E., Arzuaga-Cruz, E., Ramirez-Velez, M.,
Integration of Spatial and Spectral Information by Means of Unsupervised Extraction and Classification for Homogenous Objects Applied to Multispectral and Hyperspectral Data,
GeoRS(43), No. 4, April 2005, pp. 844-851.
IEEE Abstract. 0501
BibRef

Gu, Y., Zhang, Y., Zhang, J.,
Integration of Spatial-Spectral Information for Resolution Enhancement in Hyperspectral Images,
GeoRS(46), No. 5, May 2008, pp. 1347-1358.
IEEE DOI 0804
BibRef

Hemissi, S., Farah, I.R., Ettabaa, K.S.[K. Saheb], Solaiman, B.,
Multi-Spectro-Temporal Analysis of Hyperspectral Imagery Based on 3-D Spectral Modeling and Multilinear Algebra,
GeoRS(51), No. 1, January 2013, pp. 199-216.
IEEE DOI 1301
BibRef

Licciardi, G., Pacifici, F., Tuia, D., Prasad, S., West, T., Giacco, F., Thiel, C., Inglada, J., Christophe, E., Chanussot, J., Gamba, P.,
Decision Fusion for the Classification of Hyperspectral Data: Outcome of the 2008 GRS-S Data Fusion Contest,
GeoRS(47), No. 11, November 2009, pp. 3857-3865.
IEEE DOI 0911
BibRef

Zhao, H., Jia, G., Li, N.,
Transformation From Hyperspectral Radiance Data to Data of Other Sensors Based on Spectral Superresolution,
GeoRS(48), No. 11, November 2010, pp. 3903-3912.
IEEE DOI 1011
BibRef

Bakos, K.L., Gamba, P.,
Hierarchical Hybrid Decision Tree Fusion of Multiple Hyperspectral Data Processing Chains,
GeoRS(49), No. 1, January 2011, pp. 388-394.
IEEE DOI 1101
Fusion of results of different techniques. BibRef

Renhorn, I.[Ingmar],
Enhanced hyperspectral imaging for urban reconnaissance,
SPIE(Newsroom), May 7, 2013
DOI Link 1308
Combining images from airborne sensors enables accurate classification of materials and infrastructure in urban areas, enabling defense applications. BibRef

Wei, Q.[Qi], Bioucas-Dias, J.M., Dobigeon, N.[Nicolas], Tourneret, J.Y.[Jean-Yves],
Hyperspectral and Multispectral Image Fusion Based on a Sparse Representation,
GeoRS(53), No. 7, July 2015, pp. 3658-3668.
IEEE DOI 1503
Bayes methods BibRef
Earlier: A1, A3, A4, Only:
Bayesian fusion of multispectral and hyperspectral images with unknown sensor spectral response,
ICIP14(698-702)
IEEE DOI 1502
Decision support systems BibRef

Wei, Q.[Qi], Dobigeon, N.[Nicolas], Tourneret, J.Y.[Jean-Yves],
Fast Fusion of Multi-Band Images Based on Solving a Sylvester Equation,
IP(24), No. 11, November 2015, pp. 4109-4121.
IEEE DOI 1509
belief networks BibRef

Wei, Q.[Qi], Dobigeon, N.[Nicolas], Tourneret, J.Y.[Jean-Yves], Bioucas-Dias, J.M., Godsill, S.,
R-FUSE: Robust Fast Fusion of Multiband Images Based on Solving a Sylvester Equation,
SPLetters(23), No. 11, November 2016, pp. 1632-1636.
IEEE DOI 1609
frequency-domain analysis BibRef

Wei, Q.[Qi], Bioucas-Dias, J., Dobigeon, N.[Nicolas], Tourneret, J.Y., Chen, M., Godsill, S.,
Multiband Image Fusion Based on Spectral Unmixing,
GeoRS(54), No. 12, December 2016, pp. 7236-7249.
IEEE DOI 1612
Gaussian noise BibRef

Bieniarz, J., Cerra, D., Avbelj, J., Reinartz, P., Müller, R.,
Hyperspectral Image Resolution Enhancement Based on Spectral Unmixing and Information Fusion,
HighRes11(xx-yy).
PDF File. 1106
BibRef

Cerra, D., Bieniarz, J., Avbelj, J., Reinartz, P., Müller, R.,
Spectral Matching through Data Compression,
HighRes11(xx-yy).
PDF File. 1106
BibRef

Wang, H.Z.[Hong-Zhou], Glennie, C.L.[Craig L.],
Fusion of waveform LiDAR data and hyperspectral imagery for land cover classification,
PandRS(108), No. 1, 2015, pp. 1-11.
Elsevier DOI 1511
Full waveform LiDAR BibRef

Li, Y.H.[Yong-Hong], Wu, A.S.[Ai-Sheng], Xiong, X.X.[Xiao-Xiong],
Inter-Comparison of S-NPP VIIRS and Aqua MODIS Thermal Emissive Bands Using Hyperspectral Infrared Sounder Measurements as a Transfer Reference,
RS(8), No. 1, 2016, pp. 72.
DOI Link 1602
BibRef

Lin, B., Tao, X., Xu, M., Dong, L., Lu, J.,
Bayesian Hyperspectral and Multispectral Image Fusions via Double Matrix Factorization,
GeoRS(55), No. 10, October 2017, pp. 5666-5678.
IEEE DOI 1710
Bayes methods, estimation theory, hyperspectral imaging, image fusion, inference mechanisms, matrix decomposition, mean square error methods, optical transfer function, BibRef

Lin, B., Tao, X., Lu, J.,
Hyperspectral Image Denoising via Matrix Factorization and Deep Prior Regularization,
IP(29), No. 1, 2020, pp. 565-578.
IEEE DOI 1910
cellular neural nets, Gaussian noise, hyperspectral imaging, image denoising, impulse noise, convolutional neural networks (CNN) BibRef

Lin, C.H., Ma, F., Chi, C.Y., Hsieh, C.H.,
A Convex Optimization-Based Coupled Nonnegative Matrix Factorization Algorithm for Hyperspectral and Multispectral Data Fusion,
GeoRS(56), No. 3, March 2018, pp. 1652-1667.
IEEE DOI 1804
computational complexity, image fusion, image resolution, inverse problems, iterative methods, matrix decomposition, hyperspectral data BibRef

Ablin, R., Sulochana, C.H.[C. Helen],
Iterative-based visualization-oriented fusion scheme for hyperspectral images,
SIViP(12), No. 4, May 2018, pp. 757-765.
WWW Link. 1805
BibRef

Han, X.L.[Xiao-Lin], Yu, J.[Jing], Luo, J.Q.[Ji-Qiang], Sun, W.D.[Wei-Dong],
Hyperspectral and Multispectral Image Fusion Using Cluster-Based Multi-Branch BP Neural Networks,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Han, X.L.[Xiao-Lin], Yu, J.[Jing], Xue, J.H.[Jing-Hao], Sun, W.D.[Wei-Dong],
Hyperspectral and Multispectral Image Fusion Using Optimized Twin Dictionaries,
IP(29), 2020, pp. 4709-4720.
IEEE DOI 2003
Dictionaries, Hyperspectral imaging, Image fusion, Spatial resolution, Optimization, Bayes methods, spatial dictionary BibRef

Zhang, Y., Huynh, C.P., Ngan, K.N.,
Feature Fusion With Predictive Weighting for Spectral Image Classification and Segmentation,
GeoRS(57), No. 9, September 2019, pp. 6792-6807.
IEEE DOI 1909
Feature extraction, Image segmentation, Hyperspectral imaging, Task analysis, Training, Convolution, semantic segmentation BibRef

Ren, K.[Kai], Sun, W.W.[Wei-Wei], Meng, X.C.[Xiang-Chao], Yang, G.[Gang], Du, Q.[Qian],
Fusing China GF-5 Hyperspectral Data with GF-1, GF-2 and Sentinel-2A Multispectral Data: Which Methods Should Be Used?,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Feng, X.X.[Xiao-Xiao], He, L.[Luxiao], Cheng, Q.[Qimin], Long, X.Y.[Xiao-Yi], Yuan, Y.X.[Yu-Xin],
Hyperspectral and Multispectral Remote Sensing Image Fusion Based on Endmember Spatial Information,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Zhou, Y., Rangarajan, A., Gader, P.D.,
An Integrated Approach to Registration and Fusion of Hyperspectral and Multispectral Images,
GeoRS(58), No. 5, May 2020, pp. 3020-3033.
IEEE DOI 2005
Point spread function (PSF), hyperspectral (HS) image analysis, image fusion, nonrigid registration BibRef

Wang, Z., Chen, B., Lu, R., Zhang, H., Liu, H., Varshney, P.K.,
FusionNet: An Unsupervised Convolutional Variational Network for Hyperspectral and Multispectral Image Fusion,
IP(29), 2020, pp. 7565-7577.
IEEE DOI 2007
Hyperspectral images, multispectral images, image fusion, probabilistic generative model, convolutional neural network, meta-learning BibRef

Li, X.L.[Xue-Long], Yuan, Y.[Yue], Wang, Q.[Qi],
Hyperspectral and Multispectral Image Fusion via Nonlocal Low-Rank Tensor Approximation and Sparse Representation,
GeoRS(59), No. 1, January 2021, pp. 550-562.
IEEE DOI 2012
Tensile stress, Bayes methods, Spatial resolution, Sparse matrices, Machine learning, Image fusion, Hyperspectral (HS) image, sparse representation BibRef

Wu, S.Y.[Shi-Yong], Zhong, R.F.[Ruo-Fei], Li, Q.Y.[Qing-Yang], Qiao, K.[Ke], Zhu, Q.[Qing],
An Interband Registration Method for Hyperspectral Images Based on Adaptive Iterative Clustering,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Zhang, X.T.[Xue-Ting], Huang, W.[Wei], Wang, Q.[Qi], Li, X.L.[Xue-Long],
SSR-NET: Spatial-Spectral Reconstruction Network for Hyperspectral and Multispectral Image Fusion,
GeoRS(59), No. 7, July 2021, pp. 5953-5965.
IEEE DOI 2106
Image reconstruction, Tensile stress, Spatial resolution, Machine learning, Hyperspectral imaging, Image fusion, spatial-spectral reconstruction network (SSR-NET) BibRef

Zare, M.[Marzieh], Helfroush, M.S.[Mohammad Sadegh], Kazemi, K.[Kamran], Scheunders, P.[Paul],
Hyperspectral and Multispectral Image Fusion Using Coupled Non-Negative Tucker Tensor Decomposition,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Pan, H.[Han], Jing, Z.L.[Zhong-Liang], Leung, H.[Henry], Li, M.[Minzhe],
Hyperspectral Image Fusion and Multitemporal Image Fusion by Joint Sparsity,
GeoRS(59), No. 9, September 2021, pp. 7887-7900.
IEEE DOI 2109
Minimization, Convex functions, Spatiotemporal phenomena, Task analysis, Image fusion, Monitoring, regularization framework BibRef

Gao, J.H.[Jian-Hao], Li, J.[Jie], Jiang, M.H.[Meng-Hui],
Hyperspectral and Multispectral Image Fusion by Deep Neural Network in a Self-Supervised Manner,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Liu, N.[Na], Li, L.[Lu], Li, W.[Wei], Tao, R.[Ran], Fowler, J.E.[James E.], Chanussot, J.[Jocelyn],
Hyperspectral Restoration and Fusion With Multispectral Imagery via Low-Rank Tensor-Approximation,
GeoRS(59), No. 9, September 2021, pp. 7817-7830.
IEEE DOI 2109
Tensors, Spatial resolution, Degradation, Hyperspectral imaging, Image restoration, Interpolation, Clustering algorithms, low-rank tensor BibRef


Liu, Z.[Zhe], Zheng, Y.[Yinqiang], Han, X.H.[Xian-Hua],
Unsupervised Multispectral and Hyperspectral Image Fusion with Deep Spatial and Spectral Priors,
MLCSA20(31-45).
Springer DOI 2103
BibRef

Wang, W., Zeng, W., Huang, Y., Ding, X., Paisley, J.,
Deep Blind Hyperspectral Image Fusion,
ICCV19(4149-4158)
IEEE DOI 2004
geophysical image processing, hyperspectral imaging, image fusion, image reconstruction, image resolution, Training BibRef

Mifdal, J., Coll, B., Duran, J.,
A Variational Formulation for Hyperspectral and Multispectral Image Fusion,
ICIP18(3328-3332)
IEEE DOI 1809
Hyperspectral imaging, Geometry, Degradation, Distortion, Data integration, Hyperspectral, image fusion, pansharpening, nonlocal regularization BibRef

Zhou, H.[Haoyi], Bai, X.[Xiao], Zhou, J.[Jun], Yang, H.C.[Hai-Chuan], Liu, Y.[Yun],
Learning Graph Model for Different Dimensions Image Matching,
GbRPR15(158-167).
Springer DOI 1511
To match RGB and Hyperspectral images. BibRef

Schwind, P., Schneider, M., Müller, R.,
Improving HySpex Sensor Co-registration Accuracy using BRISK and Sensor-model based RANSAC,
LandImaging14(371-376).
DOI Link 1411
BibRef

Kotwal, K.[Ketan], Chaudhuri, S.[Subhasis],
A fast approach for fusion of hyperspectral images through redundancy elimination,
ICCVGIP10(506-511).
DOI Link 1111
BibRef

Kawakami, R.[Rei], Matsushita, Y.[Yasuyuki], Wright, J.[John], Ben-Ezra, M.[Moshe], Tai, Y.W.[Yu-Wing], Ikeuchi, K.[Katsushi],
High-resolution hyperspectral imaging via matrix factorization,
CVPR11(2329-2336).
IEEE DOI 1106
By combining a lower-resolution hyper-spectral image and a high-resolution RGB image. BibRef

Rhody, H.E.,
Enhancing spatial resolution for exploitation in hyperspectral imagery,
AIPR02(19-25).
IEEE DOI 0210
BibRef

Elaksher, A.,
Fusion of Hyperspectral Images and LIDAR-Based DEMs for Coastal Mapping,
ISPRS08(B3b: 725 ff).
PDF File. 0807
BibRef

Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Fusion of LANDSAT or Sintenil Images .


Last update:Oct 20, 2021 at 09:45:26