Improving resolution by image registration
CVGIP: Graphical Models and Image Processing
A Regularization Parameter in Discrete Ill-Posed Problems
SIAM Journal on Scientific Computing
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
Super-Resolution Imaging
Computational Methods for Inverse Problems
Computational Methods for Inverse Problems
Outlier Modeling in Image Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Super-Resolution from Image Sequences - A Review
MWSCAS '98 Proceedings of the 1998 Midwest Symposium on Systems and Circuits
Handbook of Image and Video Processing (Communications, Networking and Multimedia)
Handbook of Image and Video Processing (Communications, Networking and Multimedia)
Extraction of high-resolution frames from video sequences
IEEE Transactions on Image Processing
Robust, object-based high-resolution image reconstruction from low-resolution video
IEEE Transactions on Image Processing
Joint MAP registration and high-resolution image estimation using a sequence of undersampled images
IEEE Transactions on Image Processing
Bayesian and regularization methods for hyperparameter estimation in image restoration
IEEE Transactions on Image Processing
A computationally efficient superresolution image reconstruction algorithm
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Parameter estimation in Bayesian high-resolution image reconstruction with multisensors
IEEE Transactions on Image Processing
Fast and robust multiframe super resolution
IEEE Transactions on Image Processing
An image super-resolution algorithm for different error levels per frame
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
General choice of the regularization functional in regularized image restoration
IEEE Transactions on Image Processing
A Robust and Computationally Efficient Simultaneous Super-Resolution Scheme for Image Sequences
IEEE Transactions on Circuits and Systems for Video Technology
Estimation of the parameters in regularized simultaneous super-resolution
Pattern Recognition Letters
Adaptive multiple-frame image super-resolution based on U-curve
IEEE Transactions on Image Processing
Variational method for super-resolution optical flow
Signal Processing
Enhancing face recognition at a distance using super resolution
Proceedings of the on Multimedia and security
Face hallucination based on morphological component analysis
Signal Processing
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We derive a novel method to determine the parameters for regularized super-resolution problems, addressing both the traditional regularized super-resolution problem with single- and multiple-parameters and the simultaneous super-resolution problem with two parameters. The proposal relies on the joint maximum a posteriori (JMAP) estimation technique. The classical JMAP technique provides solutions at low computational cost, but it may be unstable and presents multiple local minima. We propose to stabilize the JMAP estimation, while achieving a cost function with a unique global solution, by assuming a gamma prior distribution for the hyperparameters. The resulting fidelity is similar to the quality provided by classical methods such as GCV, L-curve and Evidence, which are computationally expensive. Experimental results illustrate the low complexity and stability of the proposed method.