Locally competitive algorithms for sparse approximation

Proceedings - International Conference on Image Processing, ICIP

Volumn 4, Issue , 2007, Pages

  Rozell, Christopher ^a   Johnson, Don ^a   Baraniuk, Richard ^a   Olshausen, Bruno ^b  

^a RICE UNIVERSITY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Approximation methods; Image coding; Nonlinear systems; Video coding; Visual system

Indexed keywords

COST FUNCTIONS; DYNAMICAL SYSTEMS; HARDWARE; IMAGE CODING; IMAGE PROCESSING; NONLINEAR SYSTEMS; VIDEO SIGNAL PROCESSING;

ANALOG HARDWARE; APPROXIMATION METHODS; COMPETITIVE ALGORITHMS; GREEDY ALGORITHMS; NORMAL OPERATING CONDITIONS; SPARSE APPROXIMATIONS; VIDEO SEQUENCES; VISUAL SYSTEMS;

APPROXIMATION ALGORITHMS;

EID: 48149091442     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2007.4379981     Document Type: Conference Paper

References (14)

1. D.L. Donoho, 'Denoising by soft-thresholding," IEEE Trans. Info. Th., vol. 41, no. 3, pp. 613-627, May 1995.
2. R.A. DeVore, B. Jawerth, and B.J. Lucier, "Image compression through wavelet transform coding," IEEE Trans. Info. Th., vol. 38, no. 2, pp. 719?-746, March 1992.
3. E. Candès, J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Info. Th., vol. 52, no. 2, pp. 489-509, February 2006.
4. B. Olshausen and D. Field, "Sparse coding of sensory inputs," Cur. Op. Neur., vol. 14, pp. 481-487, 2004.
5. S.S. Chen, D.L. Donoho, and M.A. Saunders, "Atomic decomposition by basis pursuit," J. Sci. Comp., vol. 43, no. 1, pp. 129-159, 2001.
6. J. Tropp, "Greed is good: Algorithmic results for sparse approximation," IEEE Trans. Info. Th., vol. 50, no. 10, pp. 2231-2242, 2004.
7. B.K. Natarajan, "Sparse approximate solutions to linear systems," SIAM J. Comp., vol. 24, no. 2, pp, 227-234, April 1995.
8. S. Mallat and Z. Zhang, "Matching pursuits with time-frequency dictionaries," IEEE Trans. Sig. Proc., vol. 41, no. 12, pp. 3397-3415, December 1993.
9. N. Kingsbury and T. Reeves, "Redundant representation with complex wavelets: How to achieve sparsity," in Proc. Intl. Conf on Image Proc., 2003.
10. L. Mancera and J. J. Portilla, "LO-norm-based sparse representation through alternate projections," in Proc. Intl. Conf. Image Proc., Atlanta, GA, 2006, pp. 1749-1752.
11. M. Rehn and T. Sommer, "A network that uses few active neurones to code visual input predicts the diverse shapse of cortical receptive fields," J. Comp. Neuro., 2006.
12. C.J. Rozell, D.H Johnson, R.G. Baraniuk, and B.A. Olshausen, "Neurally plausible sparse coding via thresholding and local competition," Neur. Comp., January 2007, Submitted.
13. A. Bacciotti and L. Rosier, Liapisnov functions and stability in control theory, Springer, New York, 2001.
14. E.P. Simoncelli and W.T. Freeman, "The steerable pyramid: A flexible architecture for multi-scale derivative computation," in Proc. Intl. Conf. Image Proc., 1995.