Fast compressive imaging using scrambled block hadamard ensemble

European Signal Processing Conference

Volumn , Issue , 2008, Pages

  Gan, Lu ^a   Do, Thong T ^b   Tran, Trac D ^b  

^a BRUNEL UNIVERSITY   (United Kingdom)

^b JOHNS HOPKINS UNIVERSITY   (United States)

Author keywords

Compressed sensing; Hadamard transform; Random projections; Sparsity

Indexed keywords

COMPRESSIVE IMAGING; COMPRESSIVE SENSING; FAST SAMPLING; FOURIER; HADAMARD; HADAMARD TRANSFORMS; IMAGING PERFORMANCE; IMPLEMENTATION COST; NUMBER OF SAMPLES; NUMERICAL EXPERIMENTS; OPTICAL DOMAINS; PERFECT RECONSTRUCTION; RANDOM PROJECTIONS; SPARSITY;

ELECTRICAL ENGINEERING;

SIGNAL PROCESSING;

EID: 70349284663     PISSN: 22195491     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. E. Candes, J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Inform. Theory, vol. 52, pp. 489-509, Feb. 2006.
2. D. L. Donoho, "Compressed sensing," IEEE Trans. Inform. Theory, vol. 52, pp. 1289-1306, July 2006.
3. M. Lustig, D. D. J. Santos, and J. Pauly, "Compressed sensing MRI," IEEE Signal Processing Magazine, to be published.
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, to be published.
5. E. Candès and J. Romberg, "Robust signal recovery from incomplete observations," in Proc. ICIP, 2006, pp. 1281-1284.
6. T. T. Do, T. D. Tran, and L. Gan, "Fast compressive sampling with structually random matrices," in Proc. of ICASSP, Mar. 2008.
7. W. Hoeffding, "A combinatorial central limit theorem." The Annals of Mathematical Statistics, vol. 22, pp. 558-566, Dec. 1951.
8. S. Chatterjee, "Stein's method for concentration inequalities," Probability Theory Related Fields, vol. 138, pp. 305-321, 2007.
9. E. Candès and J. Romberg, "Sparsity and incoherence in compressive sampling," Inverse Problems, vol. 23, pp. 969-985, June 2007.
10. M. A. T. Figueiredo, R. D. Nowak, and S. J. Wright, "Gradient projection for sparse reconstruction," IEEE Journal on selected topics in Signal Processing, 2007, to appear.
11. l1-magic. [Online]. Available: http://www.l1-magic.org
12. J. A. Tropp, "Greed is good: Algorithmic results for sparse approximation," IEEE Trans. Inform. Theory, vol. 50, pp. 2231-2242, Oct. 2004.
13. E. Candes and J. Romberg, "Practical signal recovery from random projections," 2005, preprint. [Online]. Available: www.acm.caltech.edu/ emmanuel/papers/PracticalRecovery.pdf
14. L. Gan, "Block compressed sensing of natural images," Proc.Int. Conf. on Digital Signal Processing (DSP), Cardiff, UK, 2007.
15. B. C. N. Ailon, "Approximate nearest neighbors and the fast johnson-lindenstrauss transform," in Proc. of 38th STOC, 2006, pp. 557-563.
16. R. Berinde and P. Indyk. Sparse recovery using sparse random matrices. [Online]. Available: http://people.csail.mit.edu/indyk/report.pdf
17. M. G. Kuhn. Analysis of the nagravision video scrambling method. [Online]. Available: http://www.cl.cam.ac.uk/ mgk25/nagra.pdf