Compressive-projection principal component analysis for the compression of hyperspectral signatures

Data Compression Conference Proceedings

Volumn , Issue , 2008, Pages 83-92

  Fowler, James E ^a  

^a MISSISSIPPI STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPRESSED SENSING; COMPUTATIONAL BURDEN; EIGEN VECTORS; HYPER-SPECTRAL; HYPERSPECTRAL SIGNATURES; LINEAR RECONSTRUCTIONS; PERTURBATION THEORY; PRINCIPAL COMPONENTS; RANDOM PROJECTIONS; RATE-DISTORTION PERFORMANCE; RECOVERY PROCESSES; RESOURCE-CONSTRAINED; SIGNATURE VECTORS; TRANSFORM CO-EFFICIENT;

DATA COMPRESSION; FINANCIAL DATA PROCESSING; MICROWAVE ANTENNAS; PERTURBATION TECHNIQUES; SIGNAL RECONSTRUCTION;

PRINCIPAL COMPONENT ANALYSIS;

EID: 50249163226     PISSN: 10680314     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DCC.2008.26     Document Type: Conference Paper

References (10)

1. Q. Du and J. E. Fowler, "Hyperspectral image compression using JPEG2000 and principal component analysis," IEEE Geoscience and Remote Sensing Letters, vol. 4, no. 2, pp. 201-205, April 2007.
2. B. Penna, T. Tillo, E. Magii, and G. Olmo, "A new low complexity KLT for lossy hyperspectral data compression," in Proceedings of the International Geoscience and Remote Sensing Symposium, vol. 7, Denver, CO, August 2006, pp. 3525-3528.
3. E. J. Candes and M. B. Wakin, "People hearing without listening: An introduction to compressive sampling," IEEE Signal Processing Magazine, to appear.
4. B. N. Parlett, The Symmetric Eigenvalue Problem. Philadelphia, PA: Society for Industrial and Applied Mathematics, 1998.
5. P. L. Combettes, "The foundations of set theoretic estimation," Proceedings of the IEEE, vol. 81, no. 2, pp. 182-208, February 1993.
6. A. Gersho and R. M. Gray, Vector Quantization and Signal Compression. Norwell, MA: Kluwer Academic Publishers, 1992.
7. I. Johnstone and A. Y. Lu, "Sparse principal component analysis," Journal of the American Statistical Association, to appear.
8. G. H. Golub and C. F. Van Loan, Matrix Computations, 3rd ed. Baltimore, MD: The Johns Hopkins University Press, 1996.
9. R. M. Willett, M. E. Gehm, and D. J. Brady, "Multiscale reconstruction for computational spectral imaging," in Computational Imaging V, C. A. Bouman, E. L. Miller, and I. Pollak, Eds. San Jose, CA: Proc. SPIE 6498, January 2007, p. 64980L.
10. E. Candes, J. Romberg, and T. Tao, "Stable signal recovery from incomplete and inaccurate measurements," Communications on Pure and Applied Mathematics, vol. 59, no. 8, pp. 1207-1223, August 2006.