We have developed a Matlab program with graphical user interface that implements several image super-resolution methods developed in this project.
This application is availabe for the use of researchers and companies.
The Matlab application implements the super-resolution methods described in the following papers, developed for the present project:
- S. Villena, M. Vega, D. Babacan, R. Molina, and A. Katsaggelos. "Bayesian combination of sparse and non sparse priors in image superresolution,"Digital Signal Processing, vol. 23, no. 2, 530-541, 2013.
- S. Villena, M. Vega, R. Molina, and A. K. Katsaggelos, "Bayesian super-resolution image reconstruction using an l1 prior," in 6th International Symposium on Image and Signal Processing and Analysis (ISPA 2009) Best paper award, Image Processing and Analysis Track, 2009, pp. 152-157.
- S. Villena, M. Vega, D. Babacan, R. Molina, and A. Katsaggelos. Using the Kullback-Leibler divergence to combine image priors in super-resolution image reconstruction. In IEEE International Conference on Image Processing, pages 809-812. Hong-Kong (China), September 2010.
- S. D. Babacan, R. Molina, and A.K. Katsaggelos. Variational Bayesian super resolution. IEEE Transactions on Image Processing, 20(4):984-999, 2011.
Additionally, it implements other common SR methods.
Download Super-resolution software and manual (4,94 MB) version released on 07/07/2015
This program is distributed for noncommercial research purposes only, WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
If you want to do a commercial use of this software please
contact Prof. R. Molina
- Matlab R2013b in Windows 7 and Centos OS v.6.5
Super-resolution sofware user's manual (PDF 2,09 MB)