1. Jorgensen, K., J. Africano, K. Hamada, et al. "Physical properties of orbital debris from spectroscopic observations," Advances in Space Research, Vol. 34, No. 5, 1021-1025, 2004.
doi:10.1016/j.asr.2003.02.031 Google Scholar
2. Lin, R. P., B. R. Dennis, G. J. Hurford, et al. The Reuven Ramaty High-energy Solar Spectroscopic Imager (RHESSI), Springer Netherlands, 2003.
doi:10.1007/978-94-017-3452-3
3. Pham, T. H., F. Bevilacqua, T. Spott, et al. "Quantifying the absorption and reduced scattering coefficients of tissuelike turbid media over a broad spectral range with noncontact Fourier-transform hyperspectral imaging," Applied Optics, Vol. 39, No. 34, 6487-6497, 2000.
doi:10.1364/AO.39.006487 Google Scholar
4. Keshava, N. and J. F. Mustard, "Spectral unmixing," IEEE Signal Processing Magazine, Vol. 19, No. 1, 44-57, 2002.
doi:10.1109/79.974727 Google Scholar
5. Zacharakis, G., R. Favicchio, A. Garofalakis, et al. "Spectral unmixing of multi-color tissue specific in vivo fluorescence in mice," European Conference on Biomedical Optics. Optical Society of America, 6626-8, 2007. Google Scholar
6. Xu, H. and B. W. Rice, "In-vivo fluorescence imaging with a multivariate curve resolution spectral unmixing technique," Journal of Biomedical Optics, Vol. 14, No. 6, 064011-064011-9, 2009.
doi:10.1117/1.3258838 Google Scholar
7. Mansfield, J. R., K. W. Gossage, C. C. Hoyt, et al. "Autofluorescence removal, multiplexing, and automated analysis methods for in-vivo fluorescence imaging," Journal of Biomedical Optics, Vol. 10, No. 4, 041207-041207-9, 2005.
doi:10.1117/1.2032458 Google Scholar
8. Duarte, M. F., M. A. Davenport, D. Takhar, et al. "Single-pixel imaging via compressive sampling," IEEE Signal Processing Magazine, Vol. 25, No. 2, 83, 2008.
doi:10.1109/MSP.2007.914730 Google Scholar
9. Candè, E. J. and M. B. Wakin, "An introduction to compressive sampling," IEEE Signal Processing Magazine, Vol. 25, No. 2, 21-30, 2008.
doi:10.1109/MSP.2007.914731 Google Scholar
10. Soldevila, F., E. Irles, V. Durán, et al. "Single-pixel polarimetric imaging spectrometer by compressive sensing," Applied Physics B, Vol. 113, No. 4, 551-558, 2013.
doi:10.1007/s00340-013-5506-2 Google Scholar
11. Li, C., T. Sun, K. F. Kelly, et al. "A compressive sensing and unmixing scheme for hyperspectral data processing," IEEE Transactions on Image Processing, Vol. 21, No. 3, 1200-1210, 2012.
doi:10.1109/TIP.2011.2167626 Google Scholar
12. Shuai, T., X. Zhang, M. Zhang, et al. "Accuracy analysis of lunar mineral end members extraction using simulated Chang’ E-1 IIM data," Yaogan Xuebao - Journal of Remote Sensing, Vol. 16, No. 6, 1205-1221, 2012. Google Scholar
13. Nascimento, J. M. P. and J. M. B. Dias, "Vertex component analysis: A fast algorithm to unmix hyperspectral data," IEEE Transactions on Geoscience and Remote Sensing, Vol. 43, No. 4, 898-910, 2005.
doi:10.1109/TGRS.2005.844293 Google Scholar
14. Becker, S., J. Bobin, and E. J. Candès, "NESTA: A fast and accurate first-order method for sparse recovery," SIAM Journal on Imaging Sciences, Vol. 4, No. 1, 1-39, 2011.
doi:10.1137/090756855 Google Scholar
15. Zhan, Y., J. Qian, D. Wang, et al. "Multifunctional gold nanorods with ultrahigh stability and tunability for in vivo fluorescence imaging, SERS detection, and photodynamic therapy," Angewandte Chemie International Edition, Vol. 52, No. 4, 1148-1151, 2013.
doi:10.1002/anie.201207909 Google Scholar
16. Studer, V., J. Bobin, M. Chahid, et al. "Compressive fluorescence microscopy for biological and hyperspectral imaging," Proceedings of the National Academy of Sciences, Vol. 109, No. 26, E1679-E1687, 2012.
doi:10.1073/pnas.1119511109 Google Scholar