Compressive pushbroom and whiskbroom sensing for hyperspectral remote-sensing imaging

2014 IEEE International Conference on Image Processing, ICIP 2014

Volumn , Issue , 2014, Pages 684-688

  Fowler, James E ^a  

^a MISSISSIPPI STATE UNIVERSITY   (United States)

Author keywords

compressed sensing; hyperspectral imagery; remote sensing

Indexed keywords

COMPRESSED SENSING; IMAGE ACQUISITION; IMAGE PROCESSING; SATELLITE IMAGERY; SPECTROSCOPY;

DIMENSIONALITY REDUCTION; EXISTING ARCHITECTURES; HYPER-SPECTRAL IMAGERIES; HYPERSPECTRAL REMOTE SENSING; MULTIPLE SENSORS; REMOTE SENSING APPLICATIONS; SENSING PLATFORMS; SPATIAL EXTENT;

REMOTE SENSING;

EID: 84913575682     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2014.7025137     Document Type: Conference Paper

References (27)

1. D. Takhar, J. N. Laska, M. B. Wakin, M. F. Duarte, D. Baron, S. Sarvotham, K. F. Kelly, and R. G. Baraniuk, "A new compressive imaging camera architecture using optical-domain compression," in Computational Imaging IV, C. A. Bouman, E. L. Miller, and I. Pollak, Eds. San Jose, CA: Proc. SPIE 6065, January 2006, p. 606509.
2. M. B. Wakin, J. N. Laska, M. F. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. F. Kelly, and R. G. Baraniuk, "An architecture for compressive imaging," in Proceedings of the International Conference on Image Processing, Atlanta, GA, October 2006, pp. 1273-1276.
3. -, "Compressive imaging for video representation and coding," in Proceedings of the Picture Coding Symposium, Beijing, China, April 2006.
4. M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, "Single-pixel imaging via compressive sampling," IEEE Signal Processing Magazine, vol. 25, no. 2, pp. 83-91, March 2008.
5. T. Sun and K. Kelly, "Compressive sensing hyperspectral imager," in Computational Optical Sensing and Imaging, San Jose, CA, October 2009, p. CTuA5.
6. M. E. Gehm, R. John, D. J. Brady, R. M. Willett, and T. J. Schulz, "Single-shot compressive spectral imaging with a dualdisperser architecture," Optics Express, vol. 15, no. 21, pp. 14 013-14 027, October 2007.
7. G. R. Arce, D. J. Brady, L. Carin, H. Arguello, and D. S. Kittle, "Compressive coded aperture spectral imaging," IEEE Signal Processing Magazine, vol. 31, no. 1, pp. 105-115, January 2014.
8. Y. Wu, I. O. Mirza, G. R. Arce, and D. W. Prather, "Development of a digital-micromirror-device-based multishot snapshot spectral imaging system," Optics Letters, vol. 36, no. 14, pp. 2692-2694, July 2011.
9. A. Wagadarikar, R. John, R. Willett, and D. Brady, "Single disperser design for coded aperture snapshot spectral imaging," Applied Optics, vol. 47, no. 10, pp. B44-B51, April 2008.
10. Y. August, C. Vachman, Y. Rivenson, and A. Stern, "Compressive hyperspectral imaging by random separable projections in both the spatial and the spectral domains," Applied Optics, vol. 52, no. 10, pp. D46-D54, April 2013.
11. R. M. Willett, M. F. Duarte, M. A. Davenport, and R. G. Baraniuk, "Sparsity and structure in hyperspectral imaging," IEEE Signal Processing Magazine, vol. 31, no. 1, pp. 116-126, January 2014.
12. J. P. Kerekes and J. R. Schott, "Hyperspectral imaging systems," in Hyperspectral Data Exploitation: Theory and Applications, C.-I. Chang, Ed. Hoboken, NJ: John Wiley & Sons, Inc., 2007, ch. 12, pp. 19-45.
13. J. E. Fowler and Q. Du, "Anomaly detection and reconstruction from random projections," IEEE Transactions on Image Processing, vol. 21, no. 1, pp. 184-195, January 2012.
14. K. Krishnamurthy, R. Willett, and M. Raginsky, "Target detection performance bounds in compressive imaging," EURASIP Journal on Advances in Signal Processing, vol. 2012, no. 1, September 2012.
15. M. A. Davenport, P. T. Boufounos, M. B. Wakin, and R. G. Baraniuk, "Signal processing with compressive measurements," IEEE Journal of Selected Topics in Signal Processing, vol. 4, no. 2, pp. 445-460, April 2010.
16. W. Li, S. Prasad, and J. E. Fowler, "Classification and reconstruction from random projections for hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 2, pp. 833-843, February 2013.
17. M. A. Davenport, M. F. Duarte, M. B. Wakin, J. N. Laska, D. Takhar, K. F. Kelly, and R. G. Baraniuk, "The smashed filter for compressive classification and target recognition," in Computational Imaging V. San Jose, CA: Proc. SPIE 6498, January 2007, p. 64980H.
18. J. Haupt, R. Castro, R. Nowak, G. Fudge, and A. Yeh, "Compressive sampling for signal classification," in Proceedings of the 40th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, October 2006, pp. 1430-1434.
19. K. Krishnamurthy, M. Raginsky, and R. Willett, "Hyperspectral target detection from incoherent projections: Nonequiprobable targets and inhomogeneous SNR," in Proceedings of the International Conference on Image Processing, Hong Kong, September 2010, pp. 1357-1360.
20. Q. Du, J. E. Fowler, and B. Ma, "Random-projection-based dimensionality reduction and decision fusion for hyperspectral target detection," in Proceedings of the International Geoscience and Remote Sensing Symposium, Vancouver, Canada, July 2011, pp. 1790-1793.
21. J. E. Fowler, S. Mun, and E. W. Tramel, "Block-based compressed sensing of images and video," Foundations and Trends in Signal Processing, vol. 4, no. 4, pp. 297-416, March 2012.
22. T. M. Lillesand, R. W. Kiefer, and J. W. Chipman, Remote Sensing and Image Interpretation, 6th ed. Hoboken, NJ: John Wiley & Sons, Inc., 2008.
23. J. E. Fowler, "Compressive-projection principal component analysis," IEEE Transactions on Image Processing, vol. 18, no. 10, pp. 2230-2242, October 2009.
24. H. Qi and S. M. Hughes, "Invariance of principal components under low-dimensional random projection of the data," in Proceedings of the International Conference on Image Processing, Orlando, FL, October 2012, pp. 937-940.
25. J. B. Campbell and R. H. Wynne, Introduction to Remote Sensing, 5th ed. New York: The Guilford Press, 2011.
26. G. Coluccia, S. K. Kuiteing, A. Abrardo, M. Barni, and E. Magli, "Progressive compressed sensing and reconstruction of multidimensional signals using hybrid transform/prediction sparsity model," IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 2, no. 3, pp. 340-352, September 2012.
27. R. O. Green, M. L. Eastwood, T. G. C. Charles M. Sarture, M. Aronsson, B. J. Chippendale, J. A. Faust, B. E. Pavri, C. J. Chovit, M. Solis, M. R. Olah, and O. Williams, "Imaging spectroscopy and the airborne visible/infrared imaging spectrometer (AVIRIS)," Remote Sensing of Environment, vol. 65, no. 3, pp. 227-248, September 1998.