Bayesian compressive sensing using Laplace priors SD Babacan, R Molina, AK Katsaggelos IEEE Transactions on image processing 19 (1), 53-63, 2009 | 907 | 2009 |
Using deep neural networks for inverse problems in imaging: beyond analytical methods A Lucas, M Iliadis, R Molina, AK Katsaggelos IEEE Signal Processing Magazine 35 (1), 20-36, 2018 | 586 | 2018 |
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 | 355 | 2011 |
Variational Bayesian super resolution SD Babacan, R Molina, AK Katsaggelos IEEE Transactions on Image Processing 20 (4), 984-999, 2010 | 330 | 2010 |
Sparse Bayesian methods for low-rank matrix estimation SD Babacan, M Luessi, R Molina, AK Katsaggelos IEEE Transactions on Signal Processing 60 (8), 3964-3977, 2012 | 317 | 2012 |
Blind deconvolution using a variational approach to parameter, image, and blur estimation R Molina, J Mateos, AK Katsaggelos IEEE Transactions on Image Processing 15 (12), 3715-3727, 2006 | 291 | 2006 |
Variational Bayesian blind deconvolution using a total variation prior SD Babacan, R Molina, AK Katsaggelos IEEE Transactions on Image Processing 18 (1), 12-26, 2008 | 289 | 2008 |
Bayesian and regularization methods for hyperparameter estimation in image restoration R Molina, AK Katsaggelos, J Mateos IEEE transactions on image processing 8 (2), 231-246, 1999 | 277 | 1999 |
Super resolution of images and video AK Katsaggelos, R Molina, J Mateos Morgan & Claypool Publishers, 2007 | 245 | 2007 |
Parameter estimation in TV image restoration using variational distribution approximation SD Babacan, R Molina, AK Katsaggelos IEEE transactions on image processing 17 (3), 326-339, 2008 | 227 | 2008 |
Generative adversarial networks and perceptual losses for video super-resolution A Lucas, S Lopez-Tapia, R Molina, AK Katsaggelos IEEE Transactions on Image Processing 28 (7), 3312-3327, 2019 | 226 | 2019 |
Bayesian blind deconvolution with general sparse image priors SD Babacan, R Molina, MN Do, AK Katsaggelos Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 222 | 2012 |
Image restoration in astronomy: a Bayesian perspective R Molina, J Núñez, FJ Cortijo, J Mateos IEEE Signal Processing Magazine 18 (2), 11-29, 2001 | 201 | 2001 |
Bayesian resolution enhancement of compressed video CA Segall, AK Katsaggelos, R Molina, J Mateos IEEE Transactions on image processing 13 (7), 898-911, 2004 | 182 | 2004 |
High-resolution images from low-resolution compressed video CA Segall, R Molina, AK Katsaggelos IEEE Signal Processing Magazine 20 (3), 37-48, 2003 | 178 | 2003 |
Variational Bayesian image restoration with a product of spatially weighted total variation image priors G Chantas, NP Galatsanos, R Molina, AK Katsaggelos IEEE transactions on image processing 19 (2), 351-362, 2009 | 165 | 2009 |
On the hierarchical Bayesian approach to image restoration: applications to astronomical images R Molina IEEE Transactions on Pattern Analysis and Machine Intelligence 16 (11), 1122 …, 1994 | 144 | 1994 |
Audiovisual fusion: Challenges and new approaches AK Katsaggelos, S Bahaadini, R Molina Proceedings of the IEEE 103 (9), 1635-1653, 2015 | 143 | 2015 |
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 | 138 | 2013 |
Total variation super resolution using a variational approach SD Babacan, R Molina, AK Katsaggelos 2008 15th IEEE International Conference on Image Processing, 641-644, 2008 | 136 | 2008 |