REFERENCES
- Shaw, G. and Burke, H. Spectral imaging for remote sensing. Lincoln Laboratory J., 2003, 14, 3–28.
- Smith, R. ‘Introduction to hyperspectral imaging’, http://www.microimages.com/getstart/pdf/hyprspec.pdf
- Goldberg, A. C., Stann, B. and Gupta, N. Multispectral, hyperspectral, and three-dimensional imaging research at the U.S. Army Research Laboratory, Proc. Sixth International Conference of Information Fusion: Fusion 2003, Cairns, Qld, Australia, July 2003, International Society for Information Fusion, pp. 499–506.
- Yuen, P. and Bishop, G. Hyperspectral multiple approach fusion for the long range detection of low observable objects: MUF2. Proc. SPIE, 2006, 6396, 63960C.1–63960C.12.
- Vagni, F. ‘Survey of hyperspectral and multispectral imaging technologies’, RTO Technical Report TR-SET- 065-P3, NATO AC/323(SET-065)TP/44, NATO RTO, Brussels Belgium, 2007.
- Bannon, D. and Thomas, R. ‘Meeting the optical demands of next generation hyperspectral imaging spectrometers’, http://www.headwallphotonics.com/downloads/photonics_tech_briefs.pdf
- Aikio, M. ‘Hyperspectral prism grating prism imaging spectrograph ’, ScD thesis, University of Oulu, Oulu, Finland, 2001.
- Gat, N. Imaging spectroscopy using tunable filters: a review. Proc. SPIE, 2000, 4056, 50–64.
- Rajwa, B., Ahmed, W., Venkatapathi, M., Gregori, G., Jin, F., Soos, J., Trivedi, S. and Robinson, J. P. AOTF-based system for image cytometry. Proc. SPIE, 2005, 5694, 16–23.
- Fong, A. and Wachman, E. Hyperspectral Imaging for the Life Sciences and Beyond, 2008 (Laurin Publishing, Pittsfield, MA).
- Pannell, C., Wachman, E., Farkas, D., Ward, J. and Seale, W. Acousto-optic tuneable filters: advances and applications to microscopy. Proc. SPIE, 6088, 263–272.
- Manolakis, D. and Shaw, G. Detection algorithms for hyperspectral imaging applications. IEEE Signal Process. Mag., 2002, 19, 29–43.
- Stein, D., Beaven, S., Hoff, L., Winter, E., Schaum, A. and Stocker, A. Anomaly detection from hyperspectral imagery. IEEE Signal Process. Mag., 2002, 19, 58–69.
- Yu, X. L., Reed, I. S. and Stocker, A. D. Comparative performance analysis of adaptive multispectral detectors. IEEE Trans. Signal Process., 1993, 41, 2639–2655.
- Chang, C. I. and Chiang, S. S. Anomaly detection and classification for hyperspectral imagery. IEEE Trans. Geosci. Remote Sens., 2002, 40, 1314–1325.
- Muhammed, H. H. Hyperspectral crop reflectance data for characterising and estimating fungal disease severity in wheat. Biosyst. Eng., 2005, 91, 9–20.
- Kwon, H. and Nasrabadi, N. Hyperspectral anomaly detection sing kernel RX-algorithm, Proc. IEEE Int. Conf. on Image Processing: ICIP 2004, Singapore, October 2004, IEEE, pp. 3331–3334.
- Kwon, H. and Nasrabadi, N. Kernel RX-algorithm: a nonlinear anomaly detector for hyperspectral imagery. IEEE Trans. Geosci. Remote Sens., 2005, 43, 388–397.
- Yuen, P. and Bishop, G. Adaptive feature extraction techniques for subpixel target detections in hyperspectral remote sensing. Proc. SPIE, 5613, 99–110.
- Yuen, P. People tracking without prior information - a biological cortex-like neural approach. Proc. SPIE, 7119, 71 1908–711908–11.
- Duda, R. O., Hart, P. E. and Stork, D. G. Pattern Classification, 2000, 2nd edition (John Wiley & Sons, New York).
- Ibrahim, I., Yuen, P., Tsitiridis, A., Chen, T., Hong, K., Jackman, J., James, D. and Richardson, M. A. Illumination independent object recognitions using multispectral imaging technique, Proc. SPIE European Sympos. on Optics/photonics in security & defence, Toulouse, France, September 2010, SPIE.
- Yuen, P. and Bishop, G. Enhancements of target detection using atmospheric correction preprocessing techniques in hyperspectral remote sensing. Proc. SPIE, 5613, 111–118.
- Yuen, P., Ibrahim, I., Tsitiridis, A., Chen, T., Hong, K., Jackman, J., James, D. and Richardson, M. A. Classification enhancements in hyperspectral remote sensing using atmospheric correction preprocessing technique. Bul. Tekn. S&T Pertahanan, 2009, 91–99.
- Yuen, P., Chen, T., Hong, K., Tsitiridis, A., Jackman, J., James, D., Richardson, M. A., Oxford, W., Piper, J., Thomas, F. and Lightman, S. Remote detection of stress using hyperspectral imaging technique, Proc. 3rd Int. Conf. on Imaging for crime detection and prevention: ICDP-09, London, UK, December 2009, Kingston University.
- Zuzak, K. J., Schaeberle, M. D. and Lewis, E. N. Visible reflectance hyperspectral imaging: characterization of a noninvasive, in vivo system for determining tissue perfusion. Anal. Chem., 2002, 74, 2021–2028.
- Zuzak, K., Gladwin, M., Cannon, R. and Levin, I. Imaging hemoglobin oxygen saturation in sickle cell disease patients using noninvasive visible reflectance hyperspectral techniques: effects of nitric oxide. Am. J. Physiol. Heart Circ. Physiol., 2003, 285, H1183–H1189.