Pattern Recognition Letters
A Bayesian super-resolution approach to demosaicing of blurred images
EURASIP Journal on Applied Signal Processing
Iterative desensitisation of image restoration filters under wrong PSF and noise estimates
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Advances in Signal Processing
Determining the regularization parameters for super-resolution problems
Signal Processing
Rethinking Biased Estimation: Improving Maximum Likelihood and the Cramér–Rao Bound
Foundations and Trends in Signal Processing
Sequential Blind PSF Estimation and Restoration of Aerial Multispectral Images
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
International Journal of Remote Sensing
Generalized SURE for exponential families: applications to regularization
IEEE Transactions on Signal Processing
Model selection criteria for image restoration
IEEE Transactions on Neural Networks
L1 prior majorization in Bayesian image restoration
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Adaptive filter design for image deblurring by using multi-criteria blurred image information
Digital Signal Processing
IEEE Transactions on Image Processing
Image statistics and local spatial conditions for nonstationary blurred image reconstruction
Proceedings of the 29th DAGM conference on Pattern recognition
Local Bayesian image restoration using variational methods and Gamma-normal distributions
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Bayesian compressive sensing using Laplace priors
IEEE Transactions on Image Processing
Adaptive langevin sampler for separation of t-distribution modelled astrophysical maps
IEEE Transactions on Image Processing
Estimation of the parameters in regularized simultaneous super-resolution
Pattern Recognition Letters
An MLP neural net with L1 and L2 regularizers for real conditions of deblurring
EURASIP Journal on Advances in Signal Processing
Introducing dynamic prior knowledge to partially-blurred image restoration
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Double regularized bayesian estimation for blur identification in video sequences
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
IWCIA'06 Proceedings of the 11th international conference on Combinatorial Image Analysis
Bayesian reconstruction of color images acquired with a single CCD
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
Robust optic-flow estimation with bayesian inference of model and hyper-parameters
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
A Bayesian hyperparameter inference for radon-transformed image reconstruction
Journal of Biomedical Imaging - Special issue on Machine Learning in Medical Imaging
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In this paper, we propose the application of the hierarchical Bayesian paradigm to the image restoration problem. We derive expressions for the iterative evaluation of the two hyperparameters applying the evidence and maximum a posteriori (MAP) analysis within the hierarchical Bayesian paradigm. We show analytically that the analysis provided by the evidence approach is more realistic and appropriate than the MAP approach for the image restoration problem. We furthermore study the relationship between the evidence and an iterative approach resulting from the set theoretic regularization approach for estimating the two hyperparameters, or their ratio, defined as the regularization parameter. Finally the proposed algorithms are tested experimentally