Basis pursuit denoising-based image superresolution using a redundant set of atoms-Reference-Cited by-同舟云学术

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Basis pursuit denoising-based image superresolution using a redundant set of atoms

Published:2014-11-25 Issue:1 Volume:10 Page:181-188
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Sajjad Muhammad,Mehmood Irfan,Abbas Naveed,Baik Sung Wook

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Link

http://link.springer.com/content/pdf/10.1007/s11760-014-0724-6.pdf

Reference30 articles.

1. Sajjad, M., Mehmood, I., Baik, S.W.: Sparse representations-based super-resolution of key-frames extracted from frames-sequences generated by a visual sensor network. Sensors 14, 3652–3674 (2014)

2. Chen, S.S., Donoho, D.L., Saunders, M.A.: Atomic decomposition by basis pursuit. SIAM J. Sci. Comput. 20, 33–61 (1998)

3. Yang, J., Wright, J., Huang, T.S., Ma, Y.: Image super-resolution via sparse representation. IEEE Trans. Image Process. 19, 2861–2873 (2010)

4. Elad, M., Aharon, M.: Image denoising via sparse and redundant representations over learned dictionaries. IEEE Trans. Image Process. 15, 3736–3745 (2006)

5. Gill, P.R., Wang, A., Molnar, A.: The in-crowd algorithm for fast basis pursuit denoising. IEEE Trans. Signal Process. 59, 4595–4605 (2011)

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