IEEE Geoscience and Remote Sensing Magazine - June 2019 - 158

IEEE Trans. Geosci. Remote Sens., vol. 46, no. 1, pp. 237-249, 2008.
doi: 10.1109/TGRS.2007.907973.
[58]M. Frank and M. Canty, "Unsupervised change detection for
hyperspectral images," in Proc. AVIRIS Workshop, 2003, pp.
63-72.
[59] A. A. Nielsen, "The regularized iteratively reweighted mad
method for change detection in multi- and hyperspectral data,"
IEEE Trans. Image Process., vol. 16, no. 2, pp. 463-478, 2007. doi:
10.1109/TIP.2006.888195.
[60] A. A. Nielsen, "Kernel maximum autocorrelation factor and
minimum noise fraction transformations," IEEE Trans. Image
Process., vol. 20, no. 3, pp. 612-624, 2011.
[61] V. Ortiz-Rivera, M. Vélez-Reyes, and B. Roysam, "Change detection in hyperspectral imagery using temporal principal components," Proc. SPIE-Int. Soc. Opt. Eng., vol. 6233, 2006. doi:
10.1117/12.667961.
[62] S. Hemissi, I. R. Farah, K. S. Ettabaa, and B. Solaiman, "A new
spatio-temporal ICA for multi-temporal endmembers extraction and change trajectory analysis," in Piers Marrakesh Progress
in Electromagnetics Research Symp., 2011, pp. 1289-1293.
[63] S. Liu, L. Bruzzone, F. Bovolo, and P. Du, "Unsupervised hierarchical spectral analysis for change detection in hyperspectral images," in Proc. 2012 4th Workshop Hyperspectral Image
and Signal Processing (WHISPERS), 2012. doi: 10.1109/WHISPERS.2012.6874245.
[64] C. Wu, B. Du, and L. Zhang, "A subspace-based change detection method for hyperspectral images," IEEE J. Sel. Topics Appl.
Earth Observ. Remote Sens., vol. 6, no. 2, pp. 815-830, 2013. doi:
10.1109/JSTARS.2013.2241396.
[65] Q. Du, L. Wasson, and R. King, "Unsupervised linear unmixing
for change detection in multitemporal airborne hyperspectral
imagery," in Proc. 2005 Int. Workshop Analysis of Multi-Temporal
Remote Sensing Images, 2005, pp. 136-140.
[66] A. Ertürk, M. D. Iordache, and A. Plaza, "Sparse unmixing-based
change detection for multitemporal hyperspectral images," IEEE
J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 9, no. 2, pp.
708-719, 2015. doi: 10.1109/JSTARS.2015.2477431.
[67] A. Ertürk, M. D. Iordache, and A. Plaza, "Sparse unmixing with
dictionary pruning for hyperspectral change detection," IEEE
J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 10, no. 1, pp.
321-330, Jan. 2017.
[68] Y. Yuan, H. Lv, and X. Lu, "Semi-supervised change detection
method for multi-temporal hyperspectral images," Neurocomputing, vol. 148, pp. 363-375, 2015. doi: 10.1016/j.neucom
.2014.06.024.
[69] Q. Du, N. Younan, and R. King, "Change analysis for hyperspectral imagery," in Int. Workshop Analysis of Multi-temporal Remote
Sensing Images, 2007. doi: 10.1109/MULTITEMP.2007.4293052.
[70] Z. Chen and B. Wang, "Spectrally-spatially regularized low-rank
and sparse decomposition: A novel method for change detection
in multitemporal hyperspectral images," Remote Sens., vol. 9, no.
10, pp. 1-21, 2017.
[71] D. Marinelli, F. Bovolo, and L. Bruzzone, "A novel change detection method for multitemporal hyperspectral images based on
binary hyperspectral change vectors," IEEE Trans. Geosci. Remote
Sens., 2019. doi: 10.1109/TGRS.2019.2894339.

158

[72] J. Yang and W. Sun, "Automatic analysis of the slight change image for unsupervised change detection," J. Appl. Remote Sens., vol.
9, no. 1, p. 095995, 2015. doi: 10.1117/1.JRS.9.095995.
[73] S. Hemissi, I. R. Farah, K. S. Ettabaa, and B. Solaiman, "Multispectro-temporal analysis of hyperspectral imagery based on
3-D spectral modeling and multilinear algebra," IEEE Trans.
Geosci. Remote Sens., vol. 51, no. 1, pp. 199-216, 2013. doi:
10.1109/TGRS.2012.2200486.
[74] S. Henrot, J. Chanussot, and C. Jutten, "Dynamical spectral unmixing of multitemporal hyperspectral images," IEEE Trans. Image Process., vol. 25, no. 9, pp. 4443-4443, 2016.
[75] M. A. Veganzones, J. E. Cohen, R. C. Farias, J. Chanussot, and
P. Comon, "Nonnegative tensor CP decomposition of hyperspectral data," IEEE Trans. Geosci. Remote Sens., vol. 54, no. 5, pp.
2577-2588, 2016. doi: 10.1109/TGRS.2015.2503737.
[76] M. T. Eismann and J. Meola, "Hyperspectral change detection:
Methodology and challenges," in Proc. IGARSS 2008-2008
IEEE Int. Geoscience and Remote Sensing Symp., 2008, pp. II-605-
II-608.
[77] K. Vongsy and M. J. Mendenhall, "A comparative study of spectral detectors," in 3rd Workshop on Hyperspectral Image and Signal
Processing: Evolution in Remote Sensing (WHISPERS), June 2011,
pp. 1-4.
[78] Y. Du, C. Chang, H. Ren, C. C. Chang, and F. M. D'Amico,
"New hyperspectral discrimination measure for spectral characterization," Opt. Eng., vol. 43, no. 8, pp. 1777-1786, 2004. doi:
10.1117/1.1766301.
[79] M. Zanetti, F. Bovolo, and L. Bruzzone, "Rayleigh-rice mixture
parameter estimation via EM algorithm for change detection in
multispectral images," IEEE Trans. Image Process., vol. 24, no. 12,
pp. 5004-5016, 2015. doi: 10.1109/TIP.2015.2474710.
[80] A. A. Nielsen, K. Conradsen, and J. J. Simpson, "Multivariate alteration detection (MAD) and MAF postprocessing in multispectral, bitemporal image data: New approaches to change detection studies," Remote Sens. Environ., vol. 64, no. 1, pp. 1-19, 1998.
doi: 10.1016/S0034-4257(97)00162-4.
[81] N. Otsu, "A threshold selection method from gray-level histograms," IEEE Trans. Syst., Man, Cybern., vol. 9, no. 1, pp. 62-66,
Jan. 1979. doi: 10.1109/TSMC.1979.4310076.
[82] B. Jeon and D. A. Landgrebe, "Classification with spatiotemporal interpixel class dependency contexts," IEEE Trans.
Geosci. Remote Sens., vol. 30, no. 4, pp. 663-672, July 1992. doi:
10.1109/36.158859.
[83] X. L. Dal and S. Khorram, "Remotely sensed change detection
based on artificial neural networks," Photogrammetric Eng. Remote
Sens., vol. 65, no. 10, pp. 1187-1194, 1999.
[84] P. Du, S. Liu, P. Liu, K. Tan, and L. Cheng, "Sub-pixel change detection for urban land-cover analysis via multi-temporal remote
sensing images," Geospatial Inform. Sci., vol. 17, no. 1, pp. 26-38,
2014. doi: 10.1080/10095020.2014.889268.
[85] Redazione ASI. "PRISMA satellite successful launched," Agenzia Spaziale Italiana. [Online]. Available: https://www.asi.it/en/
news/prisma-satellite-successful-launched

GRS
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

JUNE 2019
https://www.asi.it/en/news/prisma-satellite-successful-launched https://www.asi.it/en/news/prisma-satellite-successful-launched
IEEE Geoscience and Remote Sensing Magazine - June 2019

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - June 2019
