Open Access
Issue |
MATEC Web Conf.
Volume 232, 2018
2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
|
|
---|---|---|
Article Number | 02037 | |
Number of page(s) | 5 | |
Section | 3D Images Reconstruction and Virtual System | |
DOI | https://doi.org/10.1051/matecconf/201823202037 | |
Published online | 19 November 2018 |
- J.W. Yang, H. Peng, L. Liu, et al. Remote sensing image restoration based on zero-norm regularized kernel estimation[J]. Optics and Precision Engineering, 22, 8 (2014) [CrossRef] [Google Scholar]
- R.Y. Tsai, T.S. Huang. Multiframe image restoration and registration[J]. CVIP, 1, 5 (1984) [Google Scholar]
- J Jiang, X.S. Zhang. A review of super-resolution reconstruction algorithms[J]. Infrared Technology, 34, 7 (2012) [Google Scholar]
- S.C. Lin, C.T. Chen. Reconstructing vehicle license plate image from low resolution images using nonuniform interpolation method[J]. IJIP, 1, 8 (2007) [Google Scholar]
- H Huang, X Fan, C Qi, et al. Face Image Super-Resolution Reconstruction Based on Recognition and Projection onto Convex Sets[J]. Journal of Computer Research & Development, 42, 8 (2005) [Google Scholar]
- E.B. Castro, M. Nakano, G.S. Perez, et al. Improvement of image super-resolution algorithms using iterative back projection[J]. IEEE Latin America Transactions, 15, 6 (2017) [Google Scholar]
- K Donaldson, G.K. Myers. Bayesian super-resolution of text in video with a text-specific bimodal prior[J]. IJDAR, 7, 9 (2005) [CrossRef] [Google Scholar]
- J. Yang, J. Wright, T.S. Huang, et al. Image super-resolution via sparse representation[J]. IEEE TIP, 19, 13 (2010) [Google Scholar]
- C.Z. Deng, W. Tian W, S.Q. Wang, et al. Super-resolution reconstruction of approximate sparsity regularized infrared images[J]. Optics and Precision Engineering, 6, 7 (2014) [Google Scholar]
- M.A. Davenport, M.B. Wakin. Analysis of orthogonal matching pursuit using the restricted isometry property[J]. IEEE Trans. on Information Theory, 56, 7 (2010) [Google Scholar]
- D. Needell, R. Vershynin. Signal recovery from incomplete and inaccurate measurements via ROMP[J]. J-STSP, 4, 7 (2013) [Google Scholar]
- T. Robert. Regression shrinkage and selection via the lasso: a retrospective[J]. Journal of the Royal Statistical Society, 73, 10 (2011) [Google Scholar]
- D.L. Donoho, Y. Tsaig, I. Drori, et al. Sparse solution of underdetermined systems of linear equations by stagewise orthogonal matching pursuit[J]. IEEE Trans. on Information Theory, 58, 28 (2012) [CrossRef] [Google Scholar]
- M. Aharon, M. Elad, A. Bruckstein A. K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation[J]. IEEE Trans. on Signal Processing, 54, 12 (2006) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.