1 |
R. S. Wagner, D. E. Waagen, and M. L. Cassabaum, "Image super resolution for improved automatic target recognition," in Proc. SPIE, vol. 5426, 2004.
|
2 |
D. Li and Steven Simske, "Example based single fra me image super resolution by support vector regression," Patten Recognition Research, vol. 5, no. 1, 2010.
|
3 |
J. van Ouwerkerk, "Image super resolution survey," Image and Vision Computing, vol. 24, no. 10, 2006.
|
4 |
W. Freeman, T. Jones, and E. Pasztor, "Example based super resolution," IEEE Computer Graphics and Applications, vol. 22, no. 2, 2002.
|
5 |
Yi Tang and Xuelong Li, "Local semi-supervised regression for single image super resolution," IEEE Int. Workshop on MMSP, 2011.
|
6 |
H. Chang, D. Yeung, and Y. Xiong, "Super resolution through neighbor embedding," in Proc. IEEE CVPR, vol. 1, 2004.
|
7 |
M. Bevilacqua, A. Roumy, and C. Guillemot, "Super-resolution using Neighbor Embedding of Back-projection residuals," in 18th International Conference on Digital Signal Processing, 2013.
|
8 |
Jili G Vadukkoot and Tinu Winson K, " A new image resolution technique using neighbor embedding," Int. Journal of Advances in Computer Science and Technology, vol. 3, no. 2, 2014.
|
9 |
N. Cristianini and J. Shawe-Taylor, "An introduction to Support Vector Machines," New York:Cambridge Univ. Press, 2000.
|
10 |
V. Vapnik, "The nature of statistical learning theory," Springer Verlag, New York, 1995.
|
11 |
C. Chang and C. Lin, LIBSVM : a library for support vector machines, 2001.
|