On single image scale-up using sparse-representations

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6920 LNCS, Issue , 2012, Pages 711-730

  Zeyde, Roman ^a   Elad, Michael ^a   Protter, Matan ^a  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM ARCHITECTURES; BICUBIC INTERPOLATION; ILL POSED; IMAGE PATCHES; INTERPOLATION SCHEMES; LOW RESOLUTION IMAGES; NOISY VERSIONS; NONLINEAR FILTER; ORIGINAL IMAGES; SCALE-UP; SINGLE IMAGES; SPARSE-LAND; TRAINING SETS;

ALGORITHMS; INTERPOLATION;

COMPUTATIONAL COMPLEXITY;

EID: 84855655878     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-27413-8_47     Document Type: Conference Paper

References (22)

1. Yang, J., Wright, J., Huang, T., Ma, Y.: Image super-resolution as sparse representation of raw image patches. In: IEEE Computer Vision and Pattern Recognition (CVPR) (June 2008)
2. Yang, J., Wright, J., Huang, T., Ma, Y.: Image super-resolution via sparse representation. IEEE Trans. on Image Processing (to appear)
3. Farsiu, S., Robinson, D., Elad, M., Milanfar, P.: Advances and Challenges in Super- Resolution. International Journal of Imaging Systems and Technology 14(2), 47-57 (2004); special issue on high-resolution image reconstruction
4. Hou, H.S., Andrews, H.C.: Cubic spline for image interpolation and digital filtering. IEEE Transactions on Signal Processing 26, 508-517 (1978)
5. Irani, M., Peleg, S.: Improving Resolution by Image Registration. CVGIP: Graphical Models and Image Processing 53, 231-239 (1991)
6. Schultz, R.R., Stevenson, R.L.: A Bayesian Approach to Image Expansion for Improved Definition. IEEE Transactions on Image Processing 3(3), 233-242 (1994)
7. Freeman, W.T., Pasztor, E.C., Carmichael, O.T.: Learning Low-Level Vision. International Journal of Computer Vision 40(1), 25-47 (2000)
8. Li, X., Orchard, M.: New Edge-Directed Interpolation. IEEE Transactions on Image Processing 10, 1521-1527 (2001)
9. Chang, H., Yeung, D.-Y., Xiong, Y.: Super-resolution through neighbor embedding. In: IEEE Conference on Computer Vision and Pattern Classification (CVPR), vol. 1, pp. 275-282 (2004)
10. Elad, M., Datsenko, D.: Example-Based Regularization Deployed to Super- Resolution Reconstruction of a Single Image. The Computer Journal 50(4), 1-16 (2007)
11. Sun, J., Xu, Z., Shum, H.: Image super-resolution using gradient profile prior. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1-8 (2008)
12. Elad, M., Aharon, M.: Image denoising via learned dictionaries and sparse representation. In: International Conference on Computer Vision and Pattern Recognition, New York, June 17-22 (2006)
13. Elad, M., Aharon, M.: Image denoising via sparse and redundant representations over learned dictionaries. IEEE Trans. on Image Processing 15(12), 3736-3745 (2006)
14. Bruckstein, A.M., Donoho, D.L., Elad, M.: From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images. SIAM Review 51(1), 34-81 (2009)
15. Elad, M.: Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing. Springer, Heidelberg (2010)
16. Wang, J., Zhu, S., Gong, Y.: Resolution enhancement based on learning the sparse association of image patches. Pattern Recognition Letters 31(1) (January 2010)
17. Lou, Y., Bertozzi, A., Soatto, S.: Direct sparse deblurring. J. Math. Imag. Vis. (August 13, 2010)
18. Zhang, X., Wu, X.: Image interpolation by adaptive 2-d autoregressive modeling and soft-decision estimation. IEEE Trans. Image Process. 17(6), 887-896 (2008)
19. Mallat, S., Yu, G.: Super-Resolution with Sparse Mixing Estimators. IEEE Trans. on Image Processing 19(11), 2889-2900 (2010)
20. Aharon, M., Elad, M., Bruckstein, A.M.: The K-SVD: An algorithm for designing of overcomplete dictionaries for sparse representation. IEEE Trans. on Signal Processing 54(11), 4311-4322 (2006)
21. Rubinstein, R., Zibulevsky, M., Elad, M.: Efficient Implementation of the K-SVD Algorithm using Batch Orthogonal Matching Pursuit, Technical Report - CS Technion (April 2008)
22. Glasner, D., Bagon, S., Irani, M.: Super-Resolution from a Single Image. In: International Conference on Computer Vision, ICCV (October 2009)