Variable density compressed image sampling

IEEE Transactions on Image Processing

Volumn 19, Issue 1, 2010, Pages 264-270

  Wang, Zhongmin ^a   Arce, Gonzalo R ^a  

^a UNIVERSITY OF DELAWARE   (United States)

Author keywords

Compressed sensing; Image reconstruction; Incoherence; Variable density sampling

Indexed keywords

APRIORI; COMPRESSED IMAGES; COMPRESSED SENSING; COMPUTATIONALLY EFFICIENT; EXTENSIVE SIMULATIONS; INCOHERENCE; LINEAR PROJECTIONS; NATURAL IMAGES; SAMPLING METHOD; SAMPLING STRATEGIES; STATISTICAL DISTRIBUTION; SUB-NYQUIST SAMPLING; TRANSFORM DOMAIN; VARIABLE DENSITY; WAVELET DOMAIN;

REPAIR; SAMPLING;

IMAGE RECONSTRUCTION;

EID: 72949108064     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2009.2032889     Document Type: Article

References (19)

1. D. Donoho, "Compressed sensing," IEEE Trans. Inf. Theory, vol.52, no.4, pp. 1289-1306, Apr. 2006.
2. E. Candés, J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Inf. Theory, vol.52, no.2, pp. 489-509, Feb. 2006.
3. M. Elad, "Optimized projections for compressed sensing," IEEE Trans. Signal Process., vol.55, no.12, pp. 5695-5702, Dec. 2007.
4. E. Candés and J. Romberg, "Sparsity and incoherence in compressive sampling," Inv. Probl., vol.23, no.3, pp. 969-985, 2007.
5. L. Gan, T. T. Do, and T. D. Tran, Fast Compressive Imaging Using Scrambled Block Hadamard Ensemble, preprint, 2008.
6. M. Lustig, D. Donoho, and J. M. Pauly, "Sparse MRI: The application of compressed sensing for rapid MR imaging," Mag. Reson. Med., vol.58, no.6, pp. 1182-1195, Dec. 2007.
7. C. Schróder, P. Bórnert, and B. Aldefeld, "Spatial excitation using variable- density spiral trajectories," J. Mag. Reson. Imag., vol.18, no.1, pp. 136-141, 2003.
8. Y. Q. Shi and H. Sun, Image and Video Compression for Multimedia Engineering. Boca Raton, FL: CRC, 1999.
9. E. Candés, "Compressive sampling," Int. Congr. Math., vol.3, pp. 1433-1452, 2006.
10. D. L. Donoho and X. Huo, "Uncertainty principles and ideal atomic decomposition," IEEE Trans. Inf. Theory, vol.47, no.7, pp. 2845-2862, Nov. 2001.
11. S. S. Chen, D. L. Donoho, and M. A. Saunders, "Atomic decomposition by basis pursuit," SIAM SCI. Comput., vol.20, no.1, pp. 33-61, Aug. 1998.
12. S. Mallat, A Wavelet Tour of Signal Processing. New York: Academic, 1998.
13. S. G. Chang, B. Yu, and M. Vetterli, "Adaptive wavelet thresholding for image denoising and compression," IEEE Trans. Image Process., vol.9, no.9, pp. 1532-1546, Sep. 2000.
14. J. K. Romberg, H. Choi, and R. G. Baraniuk, "Bayesian tree-structured image modeling using wavelet-domain hidden Markov models," IEEE Trans. Image Process., vol.10, no.7, pp. 1056-1068, Jul. 2001.
15. J. L. Prince and J. M. Links, Medical Imaging Signals and Systems. New York: Pearson Prentice, 2006.
16. S.-J. Kim, M. Lustig, and J. M. Pauly, "A fast method for designing time-optimal gradient waveforms for arbitrary k-space trajectories," IEEE Trans. Med. Imag., vol.27, no.6, pp. 866-873, Jun. 2008.
17. N. P. Pitsianis, D. J. Brady, A. Portnoy, X. Sun, T. Suleski, M. A. Fiddy, M. R. Feldman, and R. D. Tekolste, "Compressive imaging sensors," in Proc. SPIE, 1999, vol.6232.
18. J. L. Paredes, G. R. Arce, and Z. Wang, "Ultra-wideband compressed sensing: Channel estimation," IEEE J. Sel. Topics Signal Process., vol.1, no.3, pp. 383-395, Oct. 2007.
19. P. Ye, J. L. Paredes, G. R. Arce, Y. Wu, C. Chen, and D. W. Prather, "Compressive confocal microscopy," presented at the IEEE ICASSP, Taiwan, R.O.C., 2009.