Blind image restoration
Developed by Cora Beatriz Pérez Ariza and José
Manuel Llamas Sánchez under the direction of Prof. Rafael Molina and
Prof. Javier Mateos, implements the algorithms in the paper R.
Molina, J. Mateos and A. K. Katsaggelos “Blind
Deconvolution using a variational approach to parameter, image, and
blur estimation,” IEEE Trans. on Image Processing, vol. 15, no. 12,
3715-3727, December 2006.
Super resolution software
A Matlab program with graphical user
interface that implements several image super-resolution methods
developed in the project
"Super-resolución bayesiana de imágenes
aplicada a vigilancia y seguridad". It implements several SR methods including the presented in the following papers:
The software and manual can be downloaded from the Super-resolution project page.
- S. Villena, M. Vega, D. Babacan, R. Molina, and A. Katsaggelos.
"Bayesian combination of sparse and non sparse priors in image superresolution," Submitted to Digital Signal Processing, 2012.
- 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.
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.
D. Babacan, R. Molina, and A.K. Katsaggelos. Variational Bayesian super
resolution. IEEE Transactions on Image Processing, 20(4):984-999, 2011.