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Software

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.

RARSoftware       PDFManual

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:
  • 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.
  • 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.
The software and manual can be downloaded from the Super-resolution project page.

 

Visual Image Processing
 
DECSAI
 
University of Granada