| A survey of classical methods and new trends in pansharpening of multispectral images I Amro, J Mateos, M Vega, R Molina, AK Katsaggelos EURASIP Journal on Advances in Signal Processing 2011, 1-22, 2011 | 363 | 2011 |
| 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 |
| Parameter estimation in Bayesian high-resolution image reconstruction with multisensors R Molina, M Vega, J Abad, AK Katsaggelos IEEE Transactions on Image Processing 12 (12), 1655-1667, 2003 | 119 | 2003 |
| Bayesian multichannel image restoration using compound Gauss-Markov random fields R Molina, J Mateos, AK Katsaggelos, M Vega IEEE Transactions on Image Processing 12 (12), 1642-1654, 2003 | 88 | 2003 |
| 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 | 87 | 2009 |
| Variational posterior distribution approximation in Bayesian super resolution reconstruction of multispectral images R Molina, M Vega, J Mateos, AK Katsaggelos Applied and Computational Harmonic Analysis 24 (2), 251-267, 2008 | 77 | 2008 |
| 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 |
| Blind color deconvolution, normalization, and classification of histological images using general super Gaussian priors and Bayesian inference F Pérez-Bueno, M Vega, MA Sales, J Aneiros-Fernández, V Naranjo, ... Computer Methods and Programs in Biomedicine 211, 106453, 2021 | 27 | 2021 |
| Terminología y traducción MÁ Vega Jornada Panllatina de Terminologia. Perpectives i camps d’aplicació …, 1996 | 27 | 1996 |
| Fast Bayesian blind deconvolution with Huber super Gaussian priors X Zhou, M Vega, F Zhou, R Molina, AK Katsaggelos Digital Signal Processing 60, 122-133, 2017 | 24 | 2017 |
| 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 | 24 | 2016 |
| Super-resolution of multispectral images M Vega, J Mateos, R Molina, AK Katsaggelos The Computer Journal 52 (1), 153-167, 2009 | 23 | 2009 |
| A TV-based image processing framework for blind color deconvolution and classification of histological images F Pérez-Bueno, M López-Pérez, M Vega, J Mateos, V Naranjo, R Molina, ... Digital Signal Processing 101, 102727, 2020 | 21 | 2020 |
| Casos de uso M Vega Recuperado el 12, 2010 | 20 | 2010 |
| Bayesian K-SVD for H and E blind color deconvolution. Applications to stain normalization, data augmentation and cancer classification F Pérez-Bueno, JG Serra, M Vega, J Mateos, R Molina, AK Katsaggelos Computerized Medical Imaging and Graphics 97, 102048, 2022 | 19 | 2022 |
| Variational Bayesian blind color deconvolution of histopathological images N Hidalgo-Gavira, J Mateos, M Vega, R Molina, AK Katsaggelos IEEE Transactions on Image Processing 29, 2026-2036, 2019 | 19 | 2019 |
| A Bayesian super-resolution approach to demosaicing of blurred images M Vega, R Molina, AK Katsaggelos EURASIP Journal on Advances in Signal Processing 2006, 1-12, 2006 | 19 | 2006 |
| Super resolution of multispectral images using TV image models M Vega, J Mateos, R Molina, AK Katsaggelos Knowledge-Based Intelligent Information and Engineering Systems: 12th …, 2008 | 18 | 2008 |
| A comparative assessment of different methods for Landsat 7/ETM+ pansharpening VF Rodriguez-Galiano, E Pardo-Igúzquiza, M Chica-Olmo, J Mateos, ... International journal of remote sensing 33 (20), 6574-6599, 2012 | 17 | 2012 |
Rafael MolinaProfessor of Computer Science, University of GranadaDirección de correo verificada de decsai.ugr.es
