-
1
-
-
0034248782
-
An information-theoretic approach to spectral variability, similarity, and discrimination for hyperspectral image analysis
-
Chang, C., An information-theoretic approach to spectral variability, similarity, and discrimination for hyperspectral image analysis. IEEE Trans. Inf. Theory 46:5 (2000), 1927–1932.
-
(2000)
IEEE Trans. Inf. Theory
, vol.46
, Issue.5
, pp. 1927-1932
-
-
Chang, C.1
-
2
-
-
80053571096
-
Hyperspectral image classification using dictionary-based sparse representation
-
Chen, Y., Nasrabadi, N.M., Tran, T.D., Hyperspectral image classification using dictionary-based sparse representation. IEEE Trans. Geosci. Remote Sens. 49:10 (2011), 3973–3985.
-
(2011)
IEEE Trans. Geosci. Remote Sens.
, vol.49
, Issue.10
, pp. 3973-3985
-
-
Chen, Y.1
Nasrabadi, N.M.2
Tran, T.D.3
-
3
-
-
84871731919
-
Hyperspectral image classification via kernel sparse representation
-
Chen, Y., Nasrabadi, N.M., Tran, T.D., Hyperspectral image classification via kernel sparse representation. IEEE Trans. Geosci. Remote Sens. 51:1 (2013), 217–231.
-
(2013)
IEEE Trans. Geosci. Remote Sens.
, vol.51
, Issue.1
, pp. 217-231
-
-
Chen, Y.1
Nasrabadi, N.M.2
Tran, T.D.3
-
4
-
-
4644303661
-
New hyperspectral discrimination measure for spectral characterization
-
Du, Y., Chang, C.I., Ren, H., Chang, C., Jensen, J.O., New hyperspectral discrimination measure for spectral characterization. Opt. Eng. 43:8 (2004), 1777–1786.
-
(2004)
Opt. Eng.
, vol.43
, Issue.8
, pp. 1777-1786
-
-
Du, Y.1
Chang, C.I.2
Ren, H.3
Chang, C.4
Jensen, J.O.5
-
5
-
-
84903278535
-
Spectral-spatial hyperspectral image classification via multiscale adaptive sparse representation
-
Fang, L., Li, S., Kang, X., Benediktsson, J., Spectral-spatial hyperspectral image classification via multiscale adaptive sparse representation. IEEE Trans. Geosci. Remote Sens. 52:12 (2014), 7606–7618.
-
(2014)
IEEE Trans. Geosci. Remote Sens.
, vol.52
, Issue.12
, pp. 7606-7618
-
-
Fang, L.1
Li, S.2
Kang, X.3
Benediktsson, J.4
-
6
-
-
3042661357
-
Thematic map comparison: evaluating the statistical significance of differences in classification accuracy
-
Foody, G.M., Thematic map comparison: evaluating the statistical significance of differences in classification accuracy. Photogramm. Eng. Remote Sens. 70:5 (2004), 627–633.
-
(2004)
Photogramm. Eng. Remote Sens.
, vol.70
, Issue.5
, pp. 627-633
-
-
Foody, G.M.1
-
7
-
-
14644421528
-
Investigation of the random forest framework for classification hyperspectral data
-
Ham, J., Chen, Y., Crawford, M.M., Ghosh, J., Investigation of the random forest framework for classification hyperspectral data. IEEE Trans. Geosci Remote Sens. 43:3 (2005), 492–501.
-
(2005)
IEEE Trans. Geosci Remote Sens.
, vol.43
, Issue.3
, pp. 492-501
-
-
Ham, J.1
Chen, Y.2
Crawford, M.M.3
Ghosh, J.4
-
8
-
-
84890123096
-
Spatial-spectral kernel sparse representation for hyperspectral image classification
-
Liu, J., Wu, Z., Wei, Z., Xiao, L., Sun, L., Spatial-spectral kernel sparse representation for hyperspectral image classification. IEEE Sel. Top. Appl. Earth Obs. 6:6 (2013), 2462–2471.
-
(2013)
IEEE Sel. Top. Appl. Earth Obs.
, vol.6
, Issue.6
, pp. 2462-2471
-
-
Liu, J.1
Wu, Z.2
Wei, Z.3
Xiao, L.4
Sun, L.5
-
9
-
-
34047163965
-
Comparative assessment of the measures of thematic classification accuracy
-
Liu, C., Comparative assessment of the measures of thematic classification accuracy. Remote Sens. Environ. 107 (2007), 606–616.
-
(2007)
Remote Sens. Environ.
, vol.107
, pp. 606-616
-
-
Liu, C.1
-
10
-
-
0029291966
-
Sparse approximate solutions to linear systems
-
Natarajan, B.K., Sparse approximate solutions to linear systems. SIAM J. Comput. 24 (1995), 227–234.
-
(1995)
SIAM J. Comput.
, vol.24
, pp. 227-234
-
-
Natarajan, B.K.1
-
11
-
-
79956324768
-
Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment
-
Pontius, R., Millones, M., Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment. Int. J Remote Sens. 32 (2011), 4407–4429.
-
(2011)
Int. J Remote Sens.
, vol.32
, pp. 4407-4429
-
-
Pontius, R.1
Millones, M.2
-
12
-
-
84872902917
-
SSIM-inspired image restoration using sparse representation
-
Rehman, A., Rostami, M., Wang, Z., Brunet, D., Vrscay, E.R., SSIM-inspired image restoration using sparse representation. EURASIP J. Adv. Signal Process. 2012:1 (2012), 1–12.
-
(2012)
EURASIP J. Adv. Signal Process.
, vol.2012
, Issue.1
, pp. 1-12
-
-
Rehman, A.1
Rostami, M.2
Wang, Z.3
Brunet, D.4
Vrscay, E.R.5
-
13
-
-
84903270810
-
Manifold- based sparse representation for hyperspectral image classification
-
Tang, Y., Yan, H., Li, L., Manifold- based sparse representation for hyperspectral image classification. IEEE Trans. Geosci. Remote Sens. 52:12 (2014), 7738–7749.
-
(2014)
IEEE Trans. Geosci. Remote Sens.
, vol.52
, Issue.12
, pp. 7738-7749
-
-
Tang, Y.1
Yan, H.2
Li, L.3
-
14
-
-
31044447641
-
The effectiveness of spectral similarity measures for the analysis of hyperspectral imagery
-
Van Der Meer, F., The effectiveness of spectral similarity measures for the analysis of hyperspectral imagery. Int. J. Appl. Earth Obs. Geoinf. 8:1 (2006), 3–17.
-
(2006)
Int. J. Appl. Earth Obs. Geoinf.
, vol.8
, Issue.1
, pp. 3-17
-
-
Van Der Meer, F.1
-
15
-
-
1942436689
-
Image quality assessment: from error visibility to structural similarity
-
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P., Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13:4 (2004), 600–612.
-
(2004)
IEEE Trans. Image Process.
, vol.13
, Issue.4
, pp. 600-612
-
-
Wang, Z.1
Bovik, A.C.2
Sheikh, H.R.3
Simoncelli, E.P.4
-
16
-
-
84896315238
-
Feature selection via Cramer's V-test discretization for remote sensing image classification
-
Wu, B., Zhang, L., Zhao, Y., Feature selection via Cramer's V-test discretization for remote sensing image classification. IEEE Trans. Geosci Remote Sens. 52:5 (2014), 2593–2606.
-
(2014)
IEEE Trans. Geosci Remote Sens.
, vol.52
, Issue.5
, pp. 2593-2606
-
-
Wu, B.1
Zhang, L.2
Zhao, Y.3
-
17
-
-
84997836154
-
SSIM-based sparse classifier for hyperspectral imagery classification
-
Wu, B., Zhu, Y., Chen, C., Wang, X., SSIM-based sparse classifier for hyperspectral imagery classification. Proc. IGIT 2015 Int. Conf. Geo. Inform. Tech. Appl. Towards GEOSS, Jan., 16-17, Szekesfehervar, Hungary, 2015, 38–46.
-
(2015)
Proc. IGIT 2015 Int. Conf. Geo. Inform. Tech. Appl. Towards GEOSS, Jan., 16-17, Szekesfehervar, Hungary
, pp. 38-46
-
-
Wu, B.1
Zhu, Y.2
Chen, C.3
Wang, X.4
-
18
-
-
84888286393
-
Improving hyperspectral image classification using spectral information divergence
-
Zhang, E., Zhang, X., Yang, S., Improving hyperspectral image classification using spectral information divergence. IEEE Geosci. Remote Sens. Lett. 11:1 (2014), 249–253.
-
(2014)
IEEE Geosci. Remote Sens. Lett.
, vol.11
, Issue.1
, pp. 249-253
-
-
Zhang, E.1
Zhang, X.2
Yang, S.3
-
19
-
-
84905922593
-
A nonlocal weighted joint sparse representation classification method for hyperspectral imagery
-
Zhang, H., Li, J., Huang, Y., Zhang, L., A nonlocal weighted joint sparse representation classification method for hyperspectral imagery. IEEE Sel. Top. Appl. Earth Obs. 7:6 (2014), 2057–2066.
-
(2014)
IEEE Sel. Top. Appl. Earth Obs.
, vol.7
, Issue.6
, pp. 2057-2066
-
-
Zhang, H.1
Li, J.2
Huang, Y.3
Zhang, L.4
|