| Bayesian combination of sparse and non-sparse priors in image super resolution S Villena, M Vega, SD Babacan, R Molina, AK Katsaggelos Digital Signal Processing 23 (2), 530-541, 2013 | 140 | 2013 |
| Bayesian super-resolution image reconstruction using an ℓ1 prior S Villena, M Vega, R Molina, AK Katsaggelos 2009 Proceedings of 6th International Symposium on Image and Signal …, 2009 | 86 | 2009 |
| A non-stationary image prior combination in super-resolution S Villena, M Vega, R Molina, AK Katsaggelos Digital Signal Processing 32, 1-10, 2014 | 37 | 2014 |
| Using the Kullback-Leibler divergence to combine image priors in super-resolution image reconstruction S Villena, M Vega, SD Babacan, R Molina, AK Katsaggelos 2010 IEEE International Conference on Image Processing, 893-896, 2010 | 30 | 2010 |
| Bayesian super-resolution of text image sequences from low resolution observations FJ Cortijo, S Villena, R Molina, A Katsaggelos Seventh International Symposium on Signal Processing and Its Applications …, 2003 | 27 | 2003 |
| Compressive sensing super resolution from multiple observations with application to passive millimeter wave images W AlSaafin, S Villena, M Vega, R Molina, AK Katsaggelos Digital Signal Processing 50, 180-190, 2016 | 25 | 2016 |
| Estimation of high resolution images and registration parameters from low resolution observations S Villena, J Abad, R Molina, AK Katsaggelos Progress in Pattern Recognition, Image Analysis and Applications: 9th …, 2004 | 10 | 2004 |
| Image prior combination in super-resolution image registration & reconstruction S Villena, M Vega, SD Babacan, R Molina, AK Katsaggelos 2010 IEEE International Workshop on Machine Learning for Signal Processing …, 2010 | 9 | 2010 |
| Image prior combination in super-resolution image reconstruction S Villena, M Vega, R Molina, AK Katsaggelos 2010 18th European Signal Processing Conference, 616-620, 2010 | 7 | 2010 |
| Super–resolution software S Villena, M Vega, D Babacan, J Mateos, R Molina, AK Katsaggelos | 6 | 2011 |
| Image super-resolution for outdoor digital forensics. Usability and legal aspects S Villena, M Vega, J Mateos, D Rosenberg, F Murtagh, R Molina, ... Computers in industry 98, 34-47, 2018 | 5 | 2018 |
| Pmmw image super resolution from compressed sensing observations W Saafin, S Villena, M Vega, R Molina, AK Katsaggelos 2015 23rd European Signal Processing Conference (EUSIPCO), 1815-1819, 2015 | 5 | 2015 |
| A general sparse image prior combination in super-resolution S Villena, M Vega, R Molina, AK Katsaggelos 2013 18th International Conference on Digital Signal Processing (DSP), 1-6, 2013 | 3 | 2013 |
| Parameter estimation in bayesian super-resolution image reconstruction from low resolution rotated and translated images S Villena, M Vega, R Molina, AK Katsaggelos Advanced Concepts for Intelligent Vision Systems: 11th International …, 2009 | 3 | 2009 |
| Greedy Bayesian double sparsity dictionary learning JG Serra, S Villena, R Molina, AK Katsaggelos 2017 IEEE International Conference on Image Processing (ICIP), 1935-1939, 2017 | 1 | 2017 |
| Superresolution software manual S Villena, M Vega, S Babacan, J Mateos, R Molina, A Katsaggelos, ... Academic, 2015 | 1 | 2015 |
| Superresolución y reconstrucción bayesiana de imágenes a partir de imágenes de baja resolución rotadas y desplazadas. Combinación de modelos S Villena Morales Granada: Universidad de Granada, 2012 | | 2012 |
| DBase III plus: guia para usuarios expertos E Jones | | 1989 |
| La potencia de: Lotus 1-2-3, versión 2: aplicaciones de negocios RE Williams McGraw-Hill, 1989 | | 1989 |
| Organización de los datos en ficheros: ficheros secuenciales SV Morales Universidad de Granada, Centro de Informática, 1987 | | 1987 |
Rafael MolinaProfessor of Computer Science, University of GranadaCorreu electrònic verificat a decsai.ugr.es
