| A two-stage method for spectral-spatial classification of hyperspectral images | 0 | 0.34 | 2020 |
| Alternating Structure-Adapted Proximal Gradient Descent for Nonconvex Nonsmooth Block-Regularized Problems. | 0 | 0.34 | 2019 |
| Fast Robust Dejitter and Interslice Discontinuity Removal in MRI Phase Acquisitions: Application to Magnetic Resonance Elastography. | 0 | 0.34 | 2019 |
| Nonconvex Optimization for 3-Dimensional Point Source Localization Using a Rotating Point Spread Function. | 0 | 0.34 | 2019 |
| Inertial Alternating Generalized Forward-Backward Splitting for Image Colorization | 0 | 0.34 | 2019 |
| A Convex Model for Edge-Histogram Specification with Applications to Edge-Preserving Smoothing. | 0 | 0.34 | 2018 |
| Novel Sparse Recovery Algorithms for 3D Debris Localization using Rotating Point Spread Function Imagery. | 0 | 0.34 | 2018 |
| Below the Surface of the Non-local Bayesian Image Denoising Method. | 0 | 0.34 | 2017 |
| Fast and Accurate Multiplicative Decomposition for Fringe Removal in Interferometric Images. | 1 | 0.36 | 2017 |
| Guest Editorial: Scale-Space and Variational Methods. | 0 | 0.34 | 2016 |
| Bilevel Image Denoising Using Gaussianity Tests. | 5 | 0.45 | 2015 |
| A Three-stage Approach for Segmenting Degraded Color Images: Smoothing, Lifting and Thresholding (SLaT) | 4 | 0.44 | 2015 |
| A Variational Model for Color Assignment. | 4 | 0.42 | 2015 |
| Fully Smoothed ℓ 1-TV Models: Bounds for the Minimizers and Parameter Choice. | 3 | 0.49 | 2014 |
| Fast Hue and Range Preserving Histogram Specification: Theory and New Algorithms for Color Image Enhancement | 24 | 0.92 | 2014 |
| Description of the Minimizers of Least Squares Regularized with 퓁0-norm. Uniqueness of the Global Minimizer. | 0 | 0.34 | 2013 |
| On 퓁1 Data Fitting and Concave Regularization for Image Recovery. | 0 | 0.34 | 2013 |
| Exact Histogram Specification for Digital Images Using a Variational Approach | 20 | 0.87 | 2013 |
| A Fast Algorithm for Exact Histogram Specification. Simple Extension to Colour Images. | 5 | 0.46 | 2013 |
| Should we search for a global minimizer of least squares regularized with an ℓ0 penalty to get the exact solution of an under determined linear system? | 0 | 0.34 | 2011 |
| Either fit to data entries or locally to prior: the minimizers of objectives with nonsmooth nonconvex data fidelity and regularization | 0 | 0.34 | 2011 |
| A variational approach for exact histogram specification | 2 | 0.37 | 2011 |
| Multiplicative Noise Removal Using L1 Fidelity on Frame Coefficients | 64 | 1.81 | 2010 |
| Fast Two-Phase Image Deblurring Under Impulse Noise | 65 | 1.69 | 2010 |
| Fast Nonconvex Nonsmooth Minimization Methods for Image Restoration and Reconstruction | 33 | 0.89 | 2010 |
| Multiplicative Noise Cleaning via a Variational Method Involving Curvelet Coefficients | 8 | 0.70 | 2009 |
| One-iteration dejittering of digital video images | 0 | 0.34 | 2009 |
| Fast Dejittering for Digital Video Frames | 4 | 0.50 | 2009 |
| Semi-explicit Solution and Fast Minimization Scheme for an Energy with l1-Fitting and Tikhonov-Like Regularization | 1 | 0.37 | 2009 |
| Efficient Reconstruction of Piecewise Constant Images Using Nonsmooth Nonconvex Minimization | 61 | 2.14 | 2008 |
| Bounds on the minimizers of (nonconvex) regularized least-squares | 0 | 0.34 | 2007 |
| Counter-examples for Bayesian MAP restoration | 0 | 0.34 | 2007 |
| The Equivalence of Half-Quadratic Minimization and the Gradient Linearization Iteration | 41 | 1.58 | 2007 |
| Denoising of Frame Coefficients Using ℓ1 Data-Fidelity Term and Edge-Preserving Regularization. | 0 | 0.34 | 2007 |
| Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models | 169 | 7.43 | 2006 |
| Efficient Minimization Methods of Mixed l2-l1 and l1-l1 Norms for Image Restoration | 47 | 3.02 | 2006 |
| Blind identification/equalization using deterministic maximum likelihood and a partial prior on the input | 2 | 0.36 | 2006 |
| Analysis of Half-Quadratic Minimization Methods for Signal and Image Recovery | 151 | 5.09 | 2005 |
| Minimization of detail-preserving regularization functional by Newton's method with continuation | 8 | 0.58 | 2005 |
| Analysis of the Recovery of Edges in Images and Signals by Minimizing Nonconvex Regularized Least-Squares. | 55 | 2.11 | 2005 |
| Salt-and-Pepper noise removal by median-type noise detectors and detail-preserving regularization. | 282 | 12.63 | 2005 |
| Fast algorithms for l1 norm/mixed l1 and l2 norms for image restoration | 2 | 0.37 | 2005 |
| Finding the global minimum for binary image restoration | 9 | 0.62 | 2005 |
| The Use Of Super-Resolution Techniques To Reduce Slice Thickness In Functional Mri | 22 | 1.83 | 2004 |
| An iterative procedure for removing random-valued impulse noise | 82 | 2.96 | 2004 |
| Weakly Constrained Minimization: Application to the Estimation of Images and Signals Involving Constant Regions | 43 | 4.03 | 2004 |
| A Variational Approach to Remove Outliers and Impulse Noise | 266 | 13.32 | 2004 |
| Modeling anisotropic undersampling of magnetic resonance angiographies and reconstruction of a high-resolution isotropic volume using half-quadratic regularization techniques | 2 | 0.45 | 2004 |
| Efficient removing of impulsive noise based on an l/sub 1/-l/sub 2/ cost-function | 0 | 0.34 | 2003 |
| A Superresolution Framework for fMRI Sequences and Its Impact on Resulting Activation Maps | 6 | 0.64 | 2003 |
