Improved sparse coding using manifold projections

Proceedings - International Conference on Image Processing, ICIP

Volumn , Issue , 2011, Pages 1237-1240

  Ramamurthy, Karthikeyan Natesan ^a   Thiagarajan, Jayaraman J ^a   Spanias, Andreas ^a  

^a ARIZONA STATE UNIVERSITY   (United States)

Author keywords

dictionary learning; image inpainting; manifold projection; sparse representation

Indexed keywords

DATA MANIFOLDS; DATA RECOVERY; DICTIONARY LEARNING; HIGH NOISE; IMAGE INPAINTING; LOW DIMENSIONAL; MANIFOLD PROJECTION; RECONSTRUCTION ERROR; SIGNAL AND IMAGE PROCESSING; SPARSE APPROXIMATIONS; SPARSE CODING; SPARSE REPRESENTATION;

ALGORITHMS; CODES (SYMBOLS); RECOVERY;

IMAGE CODING;

EID: 84856283162     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2011.6115656     Document Type: Conference Paper

References (11)

1. J. R. Munkres, Elementary differential topology, Princeton University Press, 1966.
2. E. Saucan, E. Appleboim, and Y. Zeevi, "Sampling and reconstruction of surfaces and higher dimensional manifolds," Journal of Mathematical Imaging and Vision, vol. 30, no. 1, pp. 105-123, 2008.
3. G. Carlsson et. al., "On the local behavior of spaces of natural images," International Journal of Computer Vision, vol. 2007, 2006.
4. M. Aharon et al., "K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation," IEEE Transactions on Signal Processing, vol. 54, no. 11, pp. 4311-4322, November 2006. (Pubitemid 44637761)
5. J. J. Thiagarajan et al., "Multilevel dictionary learning for sparse representation of images," Proc. IEEE DSP/SPE Workshop, 2011.
6. M. Aharon and M. Elad, "Image denoising via sparse and redundant representations over learned dictionaries," IEEE Transactions on Image Processing, vol. 15, no. 12, pp. 3736-3745, 2006. (Pubitemid 44811686)
7. K. Yu et al., "Nonlinear learning using local coordinate coding,"Proceedings of NIPS, 2009.
8. D. L. Donoho and M. Elad, "Optimally sparse representation in general (nonorthogonal) dictionaries via l1 minimization,"Proceedings of the National Academy of Sciences of the United States of America, vol. 100, no. 5, pp. 2197-2202,March 2003. (Pubitemid 36297476)
9. S. Roweis and L. Saul, "Nonlinear dimensionality reduction by locally linear embedding," Science, pp. 2323-2326, 2000. (Pubitemid 32041578)
10. M. Grant and S. Boyd, "CVX: Matlab software for disciplined convex programming, version 1.21," http://cvxr.com/cvx, October 2010.
11. "Berkeley segmentation dataset," Available at http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/segbench/.