14.2.2.4.3 Multi-Scale, Spectral-Spatial Classification, Spatial-Spectral, Hyperspectral Data

Chapter Contents (Back)
Hyperspectral. Spectral-Spatial. Multi-Scale Classification. Spatial-Spectral.
See also Hyperspectral Target Detection.

Cui, X.M.[Xi-Min], Zheng, K.[Ke], Gao, L.R.[Lian-Ru], Zhang, B.[Bing], Yang, D.[Dong], Ren, J.C.[Jin-Chang],
Multiscale Spatial-Spectral Convolutional Network with Image-Based Framework for Hyperspectral Imagery Classification,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Yu, H.Y.[Hao-Yang], Gao, L.R.[Lian-Ru], Liao, W.Z.[Wen-Zhi], Zhang, B.[Bing], Zhuang, L.[Lina], Song, M.P.[Mei-Ping], Chanussot, J.[Jocelyn], o
Global Spatial and Local Spectral Similarity-Based Manifold Learning Group Sparse Representation for Hyperspectral Imagery Classification,
GeoRS(58), No. 5, May 2020, pp. 3043-3056.
IEEE DOI 2005
Hyperspectral imaging, Dictionaries, Manifolds, Testing, Correlation, Task analysis, Classification, group sparse representation (GSR), nonlocal self-similarity (NLSS) BibRef

Fu, H.[Hang], Sun, G.[Genyun], Ren, J.C.[Jin-Chang], Zhang, A.[Aizhu], Jia, X.P.[Xiu-Ping],
Fusion of PCA and Segmented-PCA Domain Multiscale 2-D-SSA for Effective Spectral-Spatial Feature Extraction and Data Classification in Hyperspectral Imagery,
GeoRS(60), 2022, pp. 1-14.
IEEE DOI 2112
Feature extraction, Principal component analysis, Covariance matrices, Support vector machines, Deep learning, multiscale 2-D-singular spectrum analysis (2-D-SSA) BibRef

Yu, H.Y.[Hao-Yang], Zhang, X.[Xiao], Song, M.P.[Mei-Ping], Hu, J.C.[Jiao-Chan], Guo, Q.D.[Qian-Dong], Gao, L.R.[Lian-Ru],
Hyperspectral Imagery Classification Based on Multiscale Superpixel-Level Constraint Representation,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Liu, Y.[Yao], Gao, L.R.[Lian-Ru], Xiao, C.C.[Chen-Chao], Qu, Y.[Ying], Zheng, K.[Ke], Marinoni, A.[Andrea],
Hyperspectral Image Classification Based on a Shuffled Group Convolutional Neural Network with Transfer Learning,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Sun, G.[Genyun], Fu, H.[Hang], Ren, J.C.[Jin-Chang], Zhang, A.[Aizhu], Zabalza, J.[Jaime], Jia, X.P.[Xiu-Ping], Zhao, H.M.[Hui-Min],
SpaSSA: Superpixelwise Adaptive SSA for Unsupervised Spatial-Spectral Feature Extraction in Hyperspectral Image,
Cyber(52), No. 7, July 2022, pp. 6158-6169.
IEEE DOI 2207
Feature extraction, Data mining, Trajectory, Spectral analysis, Sun, Principal component analysis, Oceanography, Feature extraction, superpixelwise adaptive SSA (SpaSSA) BibRef

Benediktsson, J.A., Kanellopoulos, I.,
Classification of Multisource and Hyperspectral Data Based on Decision Fusion,
GeoRS(37), No. 3, May 1999, pp. 1367.
IEEE Top Reference. BibRef 9905

Benediktsson, J.A., Palmason, J.A., Sveinsson, J.R.,
Classification of Hyperspectral Data From Urban Areas Based on Extended Morphological Profiles,
GeoRS(43), No. 3, March 2005, pp. 480-491.
IEEE Abstract. 0501

See also Multisource remote sensing data classification based on consensus and pruning. BibRef

Fauvel, M., Benediktsson, J.A., Chanussot, J., Sveinsson, J.R.,
Spectral and Spatial Classification of Hyperspectral Data Using SVMs and Morphological Profiles,
GeoRS(46), No. 11, November 2008, pp. 3804-3814.
IEEE DOI 0812
BibRef

Tarabalka, Y.[Yuliya], Benediktsson, J.A.[Jón Atli], Chanussot, J.[Jocelyn],
Spectral-Spatial Classification of Hyperspectral Imagery Based on Partitional Clustering Techniques,
GeoRS(47), No. 8, August 2009, pp. 2973-2987.
IEEE DOI 0907
BibRef

Ghamisi, P., Benediktsson, J.A., Sveinsson, J.R.,
Automatic Spectral-Spatial Classification Framework Based on Attribute Profiles and Supervised Feature Extraction,
GeoRS(52), No. 9, September 2014, pp. 5771-5782.
IEEE DOI 1407
data reduction BibRef

Ghamisi, P., Dalla Mura, M., Benediktsson, J.A.,
A Survey on Spectral-Spatial Classification Techniques Based on Attribute Profiles,
GeoRS(53), No. 5, May 2015, pp. 2335-2353.
IEEE DOI 1502
geophysical image processing BibRef

Ghamisi, P., Benediktsson, J.A.[Jón Atli], Ulfarsson, M.O.,
Spectral-Spatial Classification of Hyperspectral Images Based on Hidden Markov Random Fields,
GeoRS(52), No. 5, May 2014, pp. 2565-2574.
IEEE DOI 1403
Hidden Markov random field (HMRF) BibRef

Yu, H.Y.[Hao-Yang], Gao, L.R.[Lian-Ru], Li, J.[Jun], Li, S.S.[Shan Shan], Zhang, B.[Bing], Benediktsson, J.A.[Jón Atli],
Spectral-Spatial Hyperspectral Image Classification Using Subspace-Based Support Vector Machines and Adaptive Markov Random Fields,
RS(8), No. 4, 2016, pp. 355.
DOI Link 1604
BibRef

Al-khafaji, S.L., Zhou, J., Zia, A., Liew, A.W.C.,
Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images,
IP(27), No. 2, February 2018, pp. 837-850.
IEEE DOI 1712
Cameras, Feature extraction, Hyperspectral imaging, Image resolution, Transforms, spectral-spatial feature extraction BibRef

Tu, B.[Bing], Kuang, W., Zhao, G., Fei, H.Y.[Hong-Yan],
Hyperspectral Image Classification via Superpixel Spectral Metrics Representation,
SPLetters(25), No. 10, October 2018, pp. 1520-1524.
IEEE DOI 1810
Training, Measurement, Image segmentation, Entropy, Hyperspectral imaging, Shape, Hyperspectral image (HSI), spectral information divergence (SID) BibRef

Tu, B.[Bing], Li, N.Y.[Nan-Ying], Fang, L.Y.[Le-Yuan], Fei, H.Y.[Hong-Yan], He, D.B.[Dan-Bing],
Classification of Hyperspectral Images via Weighted Spatial Correlation Representation,
JVCIR(56), 2018, pp. 160-166.
Elsevier DOI 1811
Hyperspectral image, Superpixel, Joint sparse representation, Correlation coefficient BibRef

Tu, B.[Bing], Li, N.Y.[Nan-Ying], Fang, L.Y.[Le-Yuan], Yang, X.C.[Xian-Chang], Wu, J.H.[Jian-Hui],
Hyperspectral image classification with a class-dependent spatial-spectral mixed metric,
PRL(123), 2019, pp. 16-22.
Elsevier DOI 1906
Hyperspectral image, Spectral angle mapper, Spectral information divergence, Joint sparse representation, Local mean-based nearest neighbors BibRef

Yang, G.[Gan], Wang, Z.H.[Zhao-Hui],
Light-Weight Self-Supervised Contrastive Learning Network For Small Sample Hyperspectral Image Classification,
ICIP24(856-861)
IEEE DOI 2411
Training, Deep learning, Contrastive learning, Data augmentation, Feature extraction, Proposals, Labeling, small sample BibRef

Li, N.Y.[Ning-Yang], Wang, Z.H.[Zhao-Hui],
Spectral-Spatial Fused Attention Network for Hyperspectral Image Classification,
ICIP21(3832-3836)
IEEE DOI 2201
Deep learning, Correlation, Redundancy, Feature extraction, Robustness, Proposals, Hyperspectral image classification, spatial features BibRef

Fang, L.Y.[Le-Yuan], Li, S.T.[Shu-Tao], Duan, W.[Wuhui], Ren, J.C.[Jin-Chang], Benediktsson, J.A.[Jón Atli],
Classification of Hyperspectral Images by Exploiting Spectral-Spatial Information of Superpixel via Multiple Kernels,
GeoRS(53), No. 12, December 2015, pp. 6663-6674.
IEEE DOI 1512
geophysical image processing BibRef

Zhang, S.Z.[Shu-Zhen], Li, S.T.[Shu-Tao], Fu, W.[Wei], Fang, L.Y.[Lei-Yuan],
Multiscale Superpixel-Based Sparse Representation for Hyperspectral Image Classification,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

Yue, J.[Jun], Fang, L.Y.[Le-Yuan], He, M.[Min],
Spectral-Spatial Latent Reconstruction for Open-Set Hyperspectral Image Classification,
IP(31), 2022, pp. 5227-5241.
IEEE DOI 2208
Feature extraction, Image reconstruction, Training, Hyperspectral imaging, Calibration, Convolution, open-set environment BibRef

Mou, L.C.[Li-Chao], Lu, X.Q.[Xiao-Qiang], Li, X.L.[Xue-Long], Zhua, X.X.[Xiao Xiang],
Nonlocal Graph Convolutional Networks for Hyperspectral Image Classification,
GeoRS(58), No. 12, December 2020, pp. 8246-8257.
IEEE DOI 2012
Hyperspectral imaging, Convolution, Task analysis, Recurrent neural networks, Semisupervised learning, semisupervised learning BibRef

Fang, L.Y.[Le-Yuan], Li, S.T.[Shu-Tao], Kang, X.D.[Xu-Dong], Benediktsson, J.A.[Jón Atli],
Spectral-Spatial Hyperspectral Image Classification via Multiscale Adaptive Sparse Representation,
GeoRS(52), No. 12, December 2014, pp. 7738-7749.
IEEE DOI 1410
geophysical image processing
See also Class-Specific Sparse Multiple Kernel Learning for Spectral-Spatial Hyperspectral Image Classification. BibRef

Sun, H.[Hao], Zheng, X.T.[Xiang-Tao], Lu, X.Q.[Xiao-Qiang], Wu, S.Y.[Si-Yuan],
Spectral-Spatial Attention Network for Hyperspectral Image Classification,
GeoRS(58), No. 5, May 2020, pp. 3232-3245.
IEEE DOI 2005
Feature extraction, Hyperspectral imaging, Convolution, Training, Imaging, Sun, Attention, convolutional neural network (CNN), spectral-spatial feature extraction
See also Hyperspectral Image Super-Resolution with Self-Supervised Spectral-Spatial Residual Network. BibRef

Zheng, X.T.[Xiang-Tao], Sun, H.[Hao], Lu, X.Q.[Xiao-Qiang], Xie, W.[Wei],
Rotation-Invariant Attention Network for Hyperspectral Image Classification,
IP(31), 2022, pp. 4251-4265.
IEEE DOI 2207
Feature extraction, Convolution, Kernel, Imaging, Hyperspectral imaging, Interference, Data mining, attention mechanism BibRef

Hong, Q.Q.[Qing-Qing], Zhong, X.Y.[Xin-Yi], Chen, W.T.[Wei-Tong], Zhang, Z.H.[Zheng-Hua], Li, B.[Bin], Sun, H.[Hao], Yang, T.B.[Tian-Bao], Tan, C.W.[Chang-Wei],
SATNet: A Spatial Attention Based Network for Hyperspectral Image Classification,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Hong, Q.Q.[Qing-Qing], Zhong, X.Y.[Xin-Yi], Chen, W.T.[Wei-Tong], Zhang, Z.H.[Zheng-Hua], Li, B.[Bin],
Hyperspectral Image Classification Network Based on 3D Octave Convolution and Multiscale Depthwise Separable Convolution,
IJGI(12), No. 12, 2023, pp. 505.
DOI Link 2312
BibRef

Duan, P.[Puhong], Ghamisi, P.[Pedram], Kang, X.D.[Xu-Dong], Rasti, B.[Behnood], Li, S.T.[Shu-Tao], Gloaguen, R.[Richard],
Fusion of Dual Spatial Information for Hyperspectral Image Classification,
GeoRS(59), No. 9, September 2021, pp. 7726-7738.
IEEE DOI 2109
Support vector machines, Smoothing methods, Fuses, Imaging, Feature extraction, Minerals, Task analysis, Decision fusion, structural profile (SP) BibRef

Tu, B.[Bing], Zhang, X.F.[Xiao-Fei], Kang, X.D.[Xu-Dong], Zhang, G.Y.[Guo-Yun], Li, S.T.[Shu-Tao],
Density Peak-Based Noisy Label Detection for Hyperspectral Image Classification,
GeoRS(57), No. 3, March 2019, pp. 1573-1584.
IEEE DOI 1903
hyperspectral imaging, image classification, pattern clustering, remote sensing, support vector machines, support vector machines (SVMs) BibRef

Fu, W., Li, S.T.[Shu-Tao], Fang, L.Y.[Le-Yuan], Benediktsson, J.A.[Jón Atli],
Contextual Online Dictionary Learning for Hyperspectral Image Classification,
GeoRS(56), No. 3, March 2018, pp. 1336-1347.
IEEE DOI 1804
hyperspectral imaging, image classification, image representation, learning (artificial intelligence), sparse representation (SR) BibRef

Tu, B.[Bing], Zhang, X.F.[Xiao-Fei], Kang, X.D.[Xu-Dong], Wang, J.P.[Jin-Ping], Benediktsson, J.A.[Jón Atli],
Spatial Density Peak Clustering for Hyperspectral Image Classification With Noisy Labels,
GeoRS(57), No. 7, July 2019, pp. 5085-5097.
IEEE DOI 1907
Noise measurement, Training, Correlation, Clustering algorithms, Hyperspectral imaging, Labeling, Density peak (DP) clustering, support vector machines (SVMs) BibRef

Jia, S.[Sen], Zhuang, J.Y.[Jia-Yue], Deng, L.[Lin], Zhu, J.S.[Jia-Song], Xu, M.[Meng], Zhou, J.[Jun], Jia, X.P.[Xiu-Ping],
3-D Gaussian-Gabor Feature Extraction and Selection for Hyperspectral Imagery Classification,
GeoRS(57), No. 11, November 2019, pp. 8813-8826.
IEEE DOI 1911
Hyperspectral imaging, Feature extraction, Principal component analysis, Training, Task analysis, Redundancy, hyperspectral imagery BibRef

Deng, B.[Bin], Jia, S.[Sen], Shi, D.M.[Da-Ming],
Deep Metric Learning-Based Feature Embedding for Hyperspectral Image Classification,
GeoRS(58), No. 2, February 2020, pp. 1422-1435.
IEEE DOI 2001
Measurement, Training, Task analysis, Adaptation models, Feature extraction, Hyperspectral imaging, small sample set (3S) classification BibRef

Jia, S.[Sen], Deng, B.[Bin], Xie, H.M.[Hui-Min], Deng, L.[Lin],
A Gabor feature fusion framework for hyperspectral imagery classification,
ICIP17(2394-2397)
IEEE DOI 1803
Data mining, Feature extraction, Hamming distance, Hyperspectral imaging, Training, feature fusion BibRef

Zhu, J., Hu, J., Jia, S., Jia, X., Li, Q.,
Multiple 3-D Feature Fusion Framework for Hyperspectral Image Classification,
GeoRS(56), No. 4, April 2018, pp. 1873-1886.
IEEE DOI 1804
Feature extraction, Hyperspectral imaging, Shape, Surface morphology, Wavelet transforms, Feature fusion, sparse representation BibRef

Chen, Y.S.[Yu-Shi], Huang, L.B.[Ling-Bo], Zhu, L.[Lin], Yokoya, N.[Naoto], Jia, X.P.[Xiu-Ping],
Fine-Grained Classification of Hyperspectral Imagery Based on Deep Learning,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Lu, T.[Ting], Li, S.T.[Shu-Tao], Fang, L.Y.[Le-Yuan], Jia, X.P.[Xiu-Ping], Benediktsson, J.A.[Jón Atli],
From Subpixel to Superpixel: A Novel Fusion Framework for Hyperspectral Image Classification,
GeoRS(55), No. 8, August 2017, pp. 4398-4411.
IEEE DOI 1708
Data mining, Feature extraction, Geometry, Hyperspectral imaging, Probabilistic logic, Support vector machines, Decision fusion, feature fusion, hyperspectral image (HSI) classification, pixel, subpixel, superpixel BibRef

Jia, S.[Sen], Deng, B.[Bin], Zhu, J.S.[Jia-Song], Jia, X.P.[Xiu-Ping], Li, Q.Q.[Qing-Quan],
Superpixel-Based Multitask Learning Framework for Hyperspectral Image Classification,
GeoRS(55), No. 5, May 2017, pp. 2575-2588.
IEEE DOI 1705
filtering theory, hyperspectral imaging, remote sensing by radar, Gabor filters, classification performance, computational complexity, hyperspectral image classification, pixel-based spatial-spectral Schroedinger eigenmaps method, superpixel-based multitask learning framework, BibRef

Jia, S.[Sen], Deng, B.[Bin], Zhu, J.S.[Jia-Song], Jia, X.P.[Xiu-Ping], Li, Q.Q.[Qing-Quan],
Local Binary Pattern-Based Hyperspectral Image Classification With Superpixel Guidance,
GeoRS(56), No. 2, February 2018, pp. 749-759.
IEEE DOI 1802
Feature extraction, Hyperspectral imaging, Image segmentation, Merging, Support vector machines, Training, superpixel BibRef

Jia, S.[Sen], Wu, K.L.[Kui-Lin], Zhu, J.S.[Jia-Song], Jia, X.P.[Xiu-Ping],
Spectral-Spatial Gabor Surface Feature Fusion Approach for Hyperspectral Imagery Classification,
GeoRS(57), No. 2, February 2019, pp. 1142-1154.
IEEE DOI 1901
Hyperspectral imaging, Feature extraction, Clustering algorithms, Support vector machines, Image segmentation, Data mining, hyperspectral imagery classification BibRef

Jia, S.[Sen], Deng, X.L.[Xiang-Long], Zhu, J.S.[Jia-Song], Xu, M.[Meng], Zhou, J.[Jun], Jia, X.P.[Xiu-Ping],
Collaborative Representation-Based Multiscale Superpixel Fusion for Hyperspectral Image Classification,
GeoRS(57), No. 10, October 2019, pp. 7770-7784.
IEEE DOI 1910
feature extraction, Gabor filters, geophysical image processing, hyperspectral imaging, image classification, image fusion, superpixel segmentation BibRef

Jia, S.[Sen], Shen, L.L.[Lin-Lin], Li, Q.Q.[Qing-Quan],
Gabor Feature-Based Collaborative Representation for Hyperspectral Imagery Classification,
GeoRS(53), No. 2, February 2015, pp. 1118-1129.
IEEE DOI 1411
compressed sensing BibRef

Shen, L.L.[Lin-Lin], Jia, S.[Sen],
Three-Dimensional Gabor Wavelets for Pixel-Based Hyperspectral Imagery Classification,
GeoRS(49), No. 12, December 2011, pp. 5039-5046.
IEEE DOI 1201
BibRef

Jia, S.[Sen], Shen, L.L.[Lin-Lin], Zhu, J., Li, Q.Q.[Qing-Quan],
A 3-D Gabor Phase-Based Coding and Matching Framework for Hyperspectral Imagery Classification,
Cyber(48), No. 4, April 2018, pp. 1176-1188.
IEEE DOI 1804
Data mining, Feature extraction, Hyperspectral imaging, Image coding, Training, Wavelet transforms, Gabor wavelets, phase coding BibRef

Jia, S.[Sen], Deng, X.L.[Xiang-Long], Xu, M.[Meng], Zhou, J.[Jun], Jia, X.P.[Xiu-Ping],
Superpixel-Level Weighted Label Propagation for Hyperspectral Image Classification,
GeoRS(58), No. 7, July 2020, pp. 5077-5091.
IEEE DOI 2006
Hyperspectral imaging, Semisupervised learning, Image segmentation, Training, Erbium, Tuning, Hyperspectral image, superpixel segmentation BibRef

Jia, S., Xie, H., Deng, X.,
Extended Morphological Profile-based Gabor Wavelets for Hyperspectral Image Classification,
ICPR18(782-787)
IEEE DOI 1812
Feature extraction, Hyperspectral imaging, Data mining, Wavelet transforms, Surface waves BibRef

Jia, S.[Sen], Zhao, Q.Q.[Qing-Qing], Zhuang, J.Y.[Jia-Yue], Tang, D.D.[Ding-Ding], Long, Y.Q.[Ya-Qian], Xu, M.[Meng], Zhou, J.[Jun], Li, Q.Q.[Qing-Quan],
Flexible Gabor-Based Superpixel-Level Unsupervised LDA for Hyperspectral Image Classification,
GeoRS(59), No. 12, December 2021, pp. 10394-10409.
IEEE DOI 2112
Feature extraction, Hyperspectral imaging, Training, Image segmentation, Linear discriminant analysis, Data mining, superpixel segmentation BibRef

Jia, S.[Sen], Hu, J.[Jie], Zhu, J.S.[Jia-Song], Jia, X.P.[Xiu-Ping], Li, Q.Q.[Qing-Quan],
Three-Dimensional Local Binary Patterns for Hyperspectral Imagery Classification,
GeoRS(55), No. 4, April 2017, pp. 2399-2413.
IEEE DOI 1704
feature extraction BibRef

Jia, S.[Sen], Hu, J.[Jie], Xie, Y.[Yao], Shen, L.L.[Lin-Lin], Jia, X.P.[Xiu-Ping], Li, Q.Q.[Qing-Quan],
Gabor Cube Selection Based Multitask Joint Sparse Representation for Hyperspectral Image Classification,
GeoRS(54), No. 6, June 2016, pp. 3174-3187.
IEEE DOI 1606
Gabor filters BibRef

Huang, L.B.[Ling-Bo], Chen, Y.S.[Yu-Shi], He, X.[Xin], Ghamisi, P.[Pedram],
Supervised Contrastive Learning-Based Classification for Hyperspectral Image,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Huang, L.B.[Ling-Bo], Chen, Y.S.[Yu-Shi], He, X.[Xin],
Weakly Supervised Classification of Hyperspectral Image Based on Complementary Learning,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Othman, H., Qian, S.E.,
Noise Reduction of Hyperspectral Imagery Using Hybrid Spatial-Spectral Derivative-Domain Wavelet Shrinkage,
GeoRS(44), No. 2, February 2006, pp. 397-408.
IEEE DOI 0602
BibRef

Liu, J., Lu, W.,
A Probabilistic Framework for Spectral-Spatial Classification of Hyperspectral Images,
GeoRS(54), No. 9, September 2016, pp. 5375-5384.
IEEE DOI 1609
estimation theory BibRef

Zhou, Y.C.[Yi-Cong], Peng, J.T.[Jiang-Tao], Chen, C.L.P.,
Dimension Reduction Using Spatial and Spectral Regularized Local Discriminant Embedding for Hyperspectral Image Classification,
GeoRS(53), No. 2, February 2015, pp. 1082-1095.
IEEE DOI 1411
geophysical image processing BibRef

Zhang, J.[Jie], Zhang, Y.S.[Yong-Shan], Zhou, Y.C.[Yi-Cong],
Quantum-Inspired Spectral-Spatial Pyramid Network for Hyperspectral Image Classification,
CVPR23(9925-9934)
IEEE DOI 2309
BibRef

Wei, Y.T.[Yan-Tao], Zhou, Y.C.[Yi-Cong],
Spatial-Aware Network for Hyperspectral Image Classification,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Wei, Y.T.[Yan-Tao], Zhou, Y.C.[Yi-Cong], Li, H.[Hong],
Spectral-Spatial Response for Hyperspectral Image Classification,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
BibRef

Li, H.[Hong], Song, Y.[Yalong], Chen, C.L.P.[C.L. Philip],
Hyperspectral Image Classification Based on Multiscale Spatial Information Fusion,
GeoRS(55), No. 9, September 2017, pp. 5302-5312.
IEEE DOI 1709
hyperspectral imaging, image classification, image fusion, HSI classification, L1-DE, MSIF, hyperspectral image classification, local 1D embedding, multiscale spatial information fusion, multiscale strategy, BibRef

Sun, Q.[Qian], Zhao, G.R.[Guang-Rui], Fang, Y.[Yu], Fang, C.R.[Chen-Rong], Sun, L.[Le], Li, X.Y.[Xing-Ying],
MEA-EFFormer: Multiscale Efficient Attention with Enhanced Feature Transformer for Hyperspectral Image Classification,
RS(16), No. 9, 2024, pp. 1560.
DOI Link 2405
BibRef

Lu, W.[Wen], Wang, X.Y.[Xin-Yu], Sun, L.[Le], Zheng, Y.H.[Yu-Hui],
Spectral-Spatial Feature Extraction for Hyperspectral Image Classification Using Enhanced Transformer with Large-Kernel Attention,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401
BibRef

Wang, X.Y.[Xin-Yu], Sun, L.[Le], Lu, C.H.[Chu-Han], Li, B.Z.[Bao-Zhu],
A Novel Transformer Network with a CNN-Enhanced Cross-Attention Mechanism for Hyperspectral Image Classification,
RS(16), No. 7, 2024, pp. 1180.
DOI Link 2404
BibRef

Liu, J.J.[Jian-Jun], Xiao, Z.Y.[Zhi-Yong], Chen, Y.F.[Yu-Feng], Yang, J.L.[Jin-Long],
Spatial-Spectral Graph Regularized Kernel Sparse Representation for Hyperspectral Image Classification,
IJGI(6), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Sun, L.[Le], Wu, Z.B.[Ze-Bin], Wei, Z.H.[Zhi-Hui], Liu, J.J.[Jian-Jun], Li, X.X.[Xing-Xiu],
Supervised Hyperspectral Image Classification Combining Sparse Unmixing and Spatial Constraint,
CVRS12(110-115).
IEEE DOI 1302
BibRef

Zhang, S.Q.[Shao-Quan], Li, J.[Jun], Wu, Z.B.[Ze-Bin], Plaza, A.[Antonio],
Spatial Discontinuity-Weighted Sparse Unmixing of Hyperspectral Images,
GeoRS(56), No. 10, October 2018, pp. 5767-5779.
IEEE DOI 1810
Image edge detection, Hyperspectral imaging, Libraries, Optimization, Spatial resolution, spatial information BibRef

Liu, J.J.[Jian-Jun], Wu, Z.B.[Ze-Bin], Li, J.[Jun], Plaza, A.[Antonio], Yuan, Y.H.[Yun-Hao],
Probabilistic-Kernel Collaborative Representation for Spatial-Spectral Hyperspectral Image Classification,
GeoRS(54), No. 4, April 2016, pp. 2371-2384.
IEEE DOI 1604
Adaptation models BibRef

He, L.[Lin], Li, J.[Jun], Plaza, A.[Antonio], Li, Y.Q.[Yuan-Qing],
Discriminative Low-Rank Gabor Filtering for Spectral-Spatial Hyperspectral Image Classification,
GeoRS(55), No. 3, March 2017, pp. 1381-1395.
IEEE DOI 1703
Feature extraction BibRef

Liu, J.J.[Jian-Jun], Wu, Z.B.[Ze-Bin], Xiao, Z.Y.[Zhi-Yong], Yang, J.L.[Jin-Long],
Classification of Hyperspectral Images Using Kernel Fully Constrained Least Squares,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Sun, L.[Le], Wu, Z.B.[Ze-Bin], Liu, J.J.[Jian-Jun], Xiao, L.[Liang], Wei, Z.H.[Zhi-Hui],
Supervised Spectral-Spatial Hyperspectral Image Classification With Weighted Markov Random Fields,
GeoRS(53), No. 3, March 2015, pp. 1490-1503.
IEEE DOI 1402
Markov processes BibRef

Liu, H.Y.[Hong-Yi], Sun, P.P.[Pei-Pei], Du, Q.[Qian], Wu, Z.B.[Ze-Bin], Wei, Z.H.[Zhi-Hui],
Hyperspectral Image Restoration Based on Low-Rank Recovery With a Local Neighborhood Weighted Spectral-Spatial Total Variation Model,
GeoRS(57), No. 3, March 2019, pp. 1409-1422.
IEEE DOI 1903
hyperspectral imaging, image restoration, optimisation, remote sensing, spectral-spatial prior information, total variation (TV) BibRef

Zhang, S.Q.[Shao-Quan], Li, J.[Jun], Li, H.C.[Heng-Chao], Deng, C.Z.[Cheng-Zhi], Plaza, A.[Antonio],
Spectral-Spatial Weighted Sparse Regression for Hyperspectral Image Unmixing,
GeoRS(56), No. 6, June 2018, pp. 3265-3276.
IEEE DOI 1806
Complexity theory, Correlation, Hyperspectral imaging, Libraries, Sparse matrices, Hyperspectral imaging, sparse unmixing, spatially weighted unmixing BibRef

Qi, L.[Lin], Li, J.[Jie], Wang, Y.[Ying], Huang, Y.F.[Yong-Fa], Gao, X.B.[Xin-Bo],
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Hyperspectral imaging, Libraries, Sparse matrices, Collaboration, Data models, Data processing, Hyperspectral imaging, spectral-spatial-weighted unmixing BibRef

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IEEE DOI 1502
geophysical image processing BibRef

He, L.[Lin], Liu, C.Y.[Chen-Ying], Li, J.[Jun], Li, Y.Q.[Yuan-Qing], Li, S.T.[Shu-Tao], Yu, Z.L.[Zhu-Liang],
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Feature extraction, Harmonic analysis, Kernel, Power harmonic filters, Standards, Hyperspectral imaging, spectral-spatial-range filtering BibRef

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Hyperspectral imaging BibRef

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Gabor filters, feature extraction, hyperspectral imaging, image classification, image filtering, overall error probability BibRef

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See also Adaptive Multiscale Deep Fusion Residual Network for Remote Sensing Image Classification. BibRef

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Semantics, Image analysis, Feature extraction, Task analysis, Bridges, Convolution, Annotations, deep learning BibRef

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feature extraction, hyperspectral imaging, image classification, neural nets, spatial information, spectral information, spatial-spectral information BibRef

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See also Fully Dense Multiscale Fusion Network for Hyperspectral Image Classification. BibRef

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Deng, X.Z.[Xiao-Zheng], Mao, S.S.[Sha-Sha], Yang, J.Y.[Jin-Yuan], Lu, S.M.[Shi-Ming], Gou, S.P.[Shui-Ping], Zhou, Y.M.[You-Ming], Jiao, L.C.[Li-Cheng],
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Transformers, Feature extraction, Convolution, Principal component analysis, Circuits and systems, bi-directional interaction mechanism (BIM) BibRef

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Wang, J.N.[Jia-Ning], Huang, R.H.[Run-Hu], Guo, S.Y.[Si-Ying], Li, L.H.[Lin-Hao], Zhu, M.H.[Ming-Hao], Yang, S.Y.[Shu-Yuan], Jiao, L.C.[Li-Cheng],
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Convolution, Feature extraction, Kernel, Standards, Computational modeling, Training, Neural networks, multiscale convolution BibRef

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Zhu, M.H.[Ming-Hao], Jiao, L.C.[Li-Cheng], Liu, F.[Fang], Yang, S.Y.[Shu-Yuan], Wang, J.N.[Jia-Ning],
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Feature extraction, Hyperspectral imaging, Task analysis, Training, Adaptation models, Machine learning, Attention network, spectral attention BibRef

Jiao, L.C.[Li-Cheng], Liang, M.M.[Miao-Miao], Chen, H.[Huan], Yang, S.Y.[Shu-Yuan], Liu, H.Y.[Hong-Ying], Cao, X.H.[Xiang-Hai],
Deep Fully Convolutional Network-Based Spatial Distribution Prediction for Hyperspectral Image Classification,
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IEEE DOI 1710
convolution, feature extraction, hyperspectral imaging, image fusion, neural nets, statistics, HSIC, deep fully convolutional network BibRef

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Tang, X.[Xu], Meng, F.[Fanbo], Zhang, X.R.[Xiang-Rong], Cheung, Y.M.[Yiu-Ming], Ma, J.J.[Jing-Jing], Liu, F.[Fang], Jiao, L.C.[Li-Cheng],
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IEEE DOI 2103
Feature extraction, Task analysis, Convolution, Solid modeling, Technological innovation, Support vector machines, spatial-spectral features BibRef

Ma, W.P.[Wen-Ping], Yang, Q.F.[Qi-Fan], Wu, Y.[Yue], Zhao, W.[Wei], Zhang, X.R.[Xiang-Rong],
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Feng, J.[Jie], Wu, X.D.[Xian-De], Shang, R.H.[Rong-Hua], Sui, C.H.[Chen-Hong], Li, J.[Jie], Jiao, L.C.[Li-Cheng], Zhang, X.R.[Xiang-Rong],
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IEEE DOI 2106
Feature extraction, Hyperspectral imaging, Machine learning, Training, Convolutional neural networks, Adaptive systems, region search BibRef

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Ma, W.P.[Wen-Ping], Guo, Q.Q.[Qiong-Qiong], Wu, Y.[Yue], Zhao, W.[Wei], Zhang, X.R.[Xiang-Rong], Jiao, L.C.[Li-Cheng],
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Li, A.J.[Ai-Jin], Jiao, L.C.[Li-Cheng], Zhu, H.[Hao], Li, L.L.[Ling-Ling], Liu, F.[Fang],
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IEEE DOI 2112
Semantics, Feature extraction, Image segmentation, Remote sensing, Task analysis, Convolution, Spatial resolution, Boundary attention, semantic segmentation BibRef

Li, Z.[Zhaokui], Huang, L.[Lin], He, J.R.[Jin-Rong],
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Gao, Q., Lim, S., Jia, X.,
Spectral-Spatial Hyperspectral Image Classification Using a Multiscale Conservative Smoothing Scheme and Adaptive Sparse Representation,
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IEEE DOI 1910
geophysical image processing, hyperspectral imaging, image classification, image denoising, image representation, sparse representation classification (SRC) BibRef

Zhang, C.J.[Chun-Ju], Li, G.D.[Guan-Dong], Du, S.H.[Shi-Hong],
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IEEE DOI 1911
Feature extraction, Training, Convolution, Remote sensing, Convergence, Data mining, Deep learning, spectral-spatial information BibRef

Mu, C.H.[Cai-Hong], Guo, Z.[Zhen], Liu, Y.[Yi],
A Multi-Scale and Multi-Level Spectral-Spatial Feature Fusion Network for Hyperspectral Image Classification,
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Qu, L.[Lei], Zhu, X.L.[Xing-Liang], Zheng, J.N.[Jian-Nan], Zou, L.[Liang],
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Zou, L.[Liang], Zhang, Z.F.[Zhi-Fan], Du, H.J.[Hai-Jia], Lei, M.[Meng], Xue, Y.[Yong], Wang, Z.J.[Z. Jane],
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Qing, Y.H.[Yu-Hao], Liu, W.Y.[Wen-Yi],
Hyperspectral Image Classification Based on Multi-Scale Residual Network with Attention Mechanism,
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Liang, L.H.[Lian-Hui], Zhang, S.Q.[Shao-Quan], Li, J.[Jun], Plaza, A.[Antonio], Cui, Z.[Zhi],
Multi-Scale Spectral-Spatial Attention Network for Hyperspectral Image Classification Combining 2D Octave and 3D Convolutional Neural Networks,
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Liu, Y.[Yi], Zhu, J.[Jian], Feng, J.J.[Jia-Jie], Mu, C.H.[Cai-Hong],
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Liu, L.Q.[Li-Qin], Shi, Z.W.[Zhen-Wei], Pan, B.[Bin], Zhang, N.[Ning], Luo, H.L.[Huan-Lin], Lan, X.C.[Xian-Chao],
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Zhang, Y.K.[Yao-Kang], Chen, Y.J.[Yun-Jie],
Multiscale Weighted Adjacent Superpixel-Based Composite Kernel for Hyperspectral Image Classification,
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Zhang, T.Y.[Tian-Yu], Shi, C.P.[Cui-Ping], Liao, D.L.[Di-Ling], Wang, L.G.[Li-Guo],
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Shi, C.P.[Cui-Ping], Sun, J.W.[Jing-Wei], Wang, L.G.[Li-Guo],
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Pan, H.Z.[Hai-Zhu], Yan, H.[Hui], Ge, H.[Haimiao], Wang, L.G.[Li-Guo], Shi, C.P.[Cui-Ping],
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Zhang, T.Y.[Tian-Yu], Shi, C.P.[Cui-Ping], Liao, D.L.[Di-Ling], Wang, L.G.[Li-Guo],
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Shi, C.P.[Cui-Ping], Liao, D.L.[Di-Ling], Zhang, T.Y.[Tian-Yu], Wang, L.G.[Li-Guo],
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Yang, J.H.[Jing-Hui], Qin, J.[Jia], Qian, J.X.[Jin-Xi], Li, A.[Anqi], Wang, L.G.[Li-Guo],
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Pan, H.Z.[Hai-Zhu], Liu, M.[Moqi], Ge, H.[Haimiao], Wang, L.G.[Li-Guo],
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Ge, H.M.[Hai-Miao], Wang, L.G.[Li-Guo], Liu, M.[Moqi], Zhu, Y.X.[Yue-Xia], Zhao, X.Y.[Xiao-Yu], Pan, H.Z.[Hai-Zhu], Liu, Y.Z.[Yan-Zhong],
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Shi, C.P.[Cui-Ping], Sun, J.W.[Jing-Wei], Wang, T.Y.[Tian-Yi], Wang, L.G.[Li-Guo],
Hyperspectral Image Classification Based on a 3D Octave Convolution and 3D Multiscale Spatial Attention Network,
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Ma, B.[Boran], Wang, L.G.[Li-Guo], Wang, H.[Heng],
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Liu, D.X.[Dong-Xu], Han, G.L.[Guang-Liang], Liu, P.X.[Pei-Xun], Yang, H.[Hang], Chen, D.B.[Dian-Bing], Li, Q.Q.[Qing-Qing], Wu, J.J.[Jia-Jia], Wang, Y.[Yirui],
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Liu, Z.C.[Zhi-Chao], Han, G.L.[Guang-Liang], Yang, H.[Hang], Liu, P.X.[Pei-Xun], Chen, D.B.[Dian-Bing], Liu, D.X.[Dong-Xu], Deng, A.[Anping],
CCC-SSA-UNet: U-Shaped Pansharpening Network with Channel Cross-Concatenation and Spatial-Spectral Attention Mechanism for Hyperspectral Image Super-Resolution,
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Liu, D.X.[Dong-Xu], Wang, Y.R.[Yi-Rui], Liu, P.X.[Pei-Xun], Li, Q.Q.[Qing-Qing], Yang, H.[Hang], Chen, D.B.[Dian-Bing], Liu, Z.C.[Zhi-Chao], Han, G.L.[Guang-Liang],
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RS(14), No. 22, 2022, pp. xx-yy.
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Liu, D.X.[Dong-Xu], Han, G.L.[Guang-Liang], Liu, P.X.[Pei-Xun], Wang, Y.R.[Yi-Rui], Yang, H.[Hang], Chen, D.B.[Dian-Bing], Li, Q.Q.[Qing-Qing], Wu, J.J.[Jia-Jia],
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Liu, D.X.[Dong-Xu], Wang, Y.[Yirui], Liu, P.X.[Pei-Xun], Li, Q.Q.[Qing-Qing], Yang, H.[Hang], Chen, D.B.[Dian-Bing], Liu, Z.C.[Zhi-Chao], Han, G.L.[Guang-Liang],
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Liu, D.X.[Dong-Xu], Li, Q.Q.[Qing-Qing], Li, M.H.[Mei-Hui], Zhang, J.L.[Jian-Lin],
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Yang, J.Q.[Jia-Qi], Du, B.[Bo], Xu, Y.H.[Yong-Hao], Zhang, L.P.[Liang-Pei],
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IP(32), 2023, pp. 2360-2373.
IEEE DOI 2305
Feature extraction, Data mining, Filling, Kernel, Task analysis, Information retrieval, multi-scale features BibRef

Liu, D.X.[Dong-Xu], Shao, T.[Tao], Qi, G.L.[Guang-Lin], Li, M.H.[Mei-Hui], Zhang, J.L.[Jian-Lin],
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Ma, Y.X.[Yun-Xuan], Lan, Y.[Yan], Xie, Y.K.[Ya-Kun], Yu, L.X.[Lan-Xin], Chen, C.[Chen], Wu, Y.S.[Yu-Song], Dai, X.A.[Xiao-Ai],
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Gao, Q.[Qi], Yin, M.F.[Ming-Feng], Wu, X.[Xiang], Liu, D.[Di], Bo, Y.M.[Yu-Ming],
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CirSysVideo(34), No. 7, July 2024, pp. 5321-5334.
IEEE DOI 2407
Visualization, Target tracking, Accuracy, Fuses, Modulation, Transformers, Real-time systems, Visual object tracking, global feature modulation BibRef


He, M.Y.[Ming-Yi], Li, B.[Bo], Chen, H.H.[Hua-Hui],
Multi-Scale 3D Deep Convolutional Neural Network for Hyperspectral Image Classification,
ICIP17(3904-3908)
IEEE DOI 1803
Convolution, Feature extraction, Hyperspectral imaging, Kernel, Training, multi-scale BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Hyperspectral Target Detection .


Last update:Nov 26, 2024 at 16:40:19