|
| This Article | ||
| ||
| Share | ||
| Bibliographic References | ||
| Add to: | ||
| | ||
| Search | ||
| ||
| ASCII Text | x | ||
| Joshua Broadwater, Rama Chellappa, "Hybrid Detectors for Subpixel Targets," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 11, pp. 1891-1903, November, 2007. | |||
| BibTex | x | ||
| @article{ 10.1109/TPAMI.2007.1104, author = {Joshua Broadwater and Rama Chellappa}, title = {Hybrid Detectors for Subpixel Targets}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {29}, number = {11}, issn = {0162-8828}, year = {2007}, pages = {1891-1903}, doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2007.1104}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Hybrid Detectors for Subpixel Targets IS - 11 SN - 0162-8828 SP1891 EP1903 EPD - 1891-1903 A1 - Joshua Broadwater, A1 - Rama Chellappa, PY - 2007 KW - Target detection KW - subspace detectors KW - hyperspectral data KW - spectral mixture models VL - 29 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
[1] D. Manolakis, C. Siracusa, and G. Shaw, “Hyperspectral Subpixel Target Detection Using the Linear Mixing Model,” IEEE Trans. Geoscience and Remote Sensing, vol. 39, no. 7, pp. 1392-1409, July 2001.
[2] B. Hapke, Introduction to the Theory of Reflectance and Emittance Spectroscopy, pp. 278-279. Cambridge Univ. Press, 1993.
[3] J.C. Harsanyi and C.-I. Chang, “Hyperspectral Image Classification and Dimensionality Reduction: An Orthogonal Subspace Projection Approach,” IEEE Trans. Geoscience and Remote Sensing, vol. 32, no. 4, pp. 779-785, July 1994.
[4] C.-I. Chang and D.C. Heinz, “Constrained Subpixel Target Detection for Remotely Sensed Imagery,” IEEE Trans. Geoscience and Remote Sensing, vol. 38, no. 3, pp. 1144-1159, May 2000.
[5] D.C. Heinz and C.-I. Chang, “Fully Constrained Least Squares Linear Spectral Mixture Analysis Method for Material Quantification in Hyperspectral Imagery,” IEEE Trans. Geoscience and Remote Sensing, vol. 39, no. 3, pp. 529-545, Mar. 2001.
[6] H. Ren, Q. Du, and J. Jensen, “Constrained Weighted Least Squares Approaches for Target Detection and Classification in Hyperspectral Imagery,” Proc. IEEE Int'l Geoscience and Remote Sensing Symp., pp. 3426-3428, June 2002.
[7] S. Kraut, L.L. Scharf, and R.W. Butler, “The Adaptive Coherence Estimator: A Uniformly Most-Powerful-Invariant Adaptive Detection Statistic,” IEEE Trans. Signal Processing, vol. 53, no. 2, pp. 427-438, Feb. 2005.
[8] D. Manolakis and G. Shaw, “Detection Algorithms for Hyperspectral Imaging Applications,” IEEE Signal Processing Magazine, vol. 19, no. 1, pp. 29-43, Jan. 2002.
[9] D.W. Stein, S.G. Beaven, L.E. Hoff, E.M. Winter, A.P. Shaum, and A.D. Stocker, “Anomaly Detection from Hyperspectral Imagery,” IEEE Signal Processing Magazine, vol. 19, no. 1, pp. 58-69, Jan. 2002.
[10] S. Johnson, “The Constrained Signal Detector,” IEEE Trans. Geoscience and Remote Sensing, vol. 40, no. 6, pp. 1326-1337, June 2002.
[11] J. Boardman, “Inversion of High Spectral Resolution Data,” Proc. SPIE Conf. Imaging Spectrometry of the Terrestrial Environment, vol. 1298, pp. 222-233, 1990.
[12] J.J. Settle and N.A. Drake, “Linear Mixing and Estimation of Ground Cover Proportions,” Int'l J. Remote Sensing, vol. 14, no. 6, pp. 1159-1177, 1993.
[13] E.A. Ashton and A. Schaum, “Algorithms for the Detection of Sub-Pixel Targets in Multispectral Imagery,” Photogrammetric Eng. and Remote Sensing, pp. 723-731, July 1998.
[14] K.H. Haskell and R.J. Hansen, “An Algorithm for Linear Least Squares Problems with Equality and Non-Negativity Constraints Generalized,” Math. Programming, vol. 21, pp. 98-118, 1981.
[15] E.J. Kelly, “An Adaptive Detection Algorithm,” IEEE Trans. Aerospace and Electronic Systems, vol. 22, pp. 115-127, Mar. 1986.
[16] S. Kraut and L.L. Scharf, “The CFAR Adaptive Sub-Space Detector Is a Scale-Invariant GLRT,” IEEE Trans. Signal Processing, vol. 47, pp. 2538-2541, Sept. 1999.
[17] S. Kraut, L. Scharf, and L.T. McWhorter, “Adaptive Subspace Detectors,” IEEE Trans. Signal Processing, vol. 49, no. 1, pp. 1-16, Jan. 2001.
[18] J. Broadwater, R. Meth, and R. Chellappa, “A Hybrid Algorithm for Subpixel Detection in Hyperspectral Imagery,” Proc. IEEE Int'l Geoscience and Remote Sensing Symp., vol. 3, pp. 1601-1604, 2004.
[19] M.E. Winter, “Fast Autonomous Spectral Endmember Determination in Hyperspectral Data,” Proc. 13th Int'l Conf. Applied Geologic Remote Sensing, vol. II, pp. 337-344, 1999.
[20] J.M. Grossmann, J. Bowles, D. Haas, J.A. Antoniades, M.R. Grunes, P. Palmadesso, D. Gillis, K.Y. Tsang, M. Baumback, M. Daniel, J. Fisher, and I. Triandaf, “Hyperspectral Analysis and Target Detection System for the Adaptive Spectral Reconnaissance Program (ASRP),” Proc. SPIE Conf. Algorithms for Multispectral and Hyperspectral Imagery IV, vol. 3372, pp. 2-13, Apr.13-14, 1998.
[21] R.A. Neville, K. Staenz, T. Szeredi, J. Lefebvre, and P. Hauff, “Automatic Endmember Extraction from Hyperspectral Data for Mineral Exploration,” Proc. Fourth Int'l Airborne Remote Sensing Conf. and Exhibition/21st Canadian Symp. Remote Sensing, pp. 891-896, June 1999.
[22] A. Plaza, P. Martinez, R. Perez, and J. Plaza, “Spatial/Spectral Endmember Extraction by Multidimensional Morphological Operations,” IEEE Trans. Geoscience and Remote Sensing, vol. 40, pp.2025-2041, Sept. 2002.
[23] C.A. Bateson, G.P. Asner, and C.A. Wessman, “Endmember Bundles: A New Approach to Incorporating Endmember Variability into Spectral Mixture Analysis,” IEEE Trans. Geoscience and Remote Sensing, vol. 38, pp. 1083-1094, Mar. 2000.
[24] A. Plaza, P. Martinez, R. Perez, and J. Plaza, “A Quantitative and Comparative Analysis of Endmember Extraction Algorithms from Hyperspectral Data,” IEEE Trans. Geoscience and Remote Sensing, vol. 42, no. 3, Mar. 2004.
[25] J. Harsanyi, W. Farrand, and C.-I. Chang, “Determining the Number and Identity of Spectral Endmembers: An Integrated Approach Using Neyman-Pearson Eigenthresholding and Iterative Constrained RMS Error Minimization,” Proc. Ninth Thematic Conf. Geologic Remote Sensing, Feb. 1993.
[26] C.-I. Chang and Q. Du, “Estimation of Number of Spectrally Distinct Signal Sources in Hyperspectral Imagery,” IEEE Trans. Geoscience and Remote Sensing, vol. 42, no. 3, pp. 608-619, Mar. 2004.
[27] G.P. Anderson, B. Pukall, C.L. Allred, L.S. Jeong, M. Hoke, J.H. Chetwynd, S.M. Adler-Golden, A. Berk, L.S. Bernstein, S.C. Richtsmeier, P.K. Acharya, and M.W. Matthew, “FLAASH and MODTRAN4: State-of-the-Art Atmospheric Correction for Hyperspectral Data,” Proc. IEEE Aerospace Conf., vol. 4, pp. 177-181, Mar. 1999.

