Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
On Discontinuity-Adaptive Smoothness Priors in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Variational Approach to Remove Outliers and Impulse Noise
Journal of Mathematical Imaging and Vision
A Predual Proximal Point Algorithm Solving a Non Negative Basis Pursuit Denoising Model
International Journal of Computer Vision
An Adaptive Method for Recovering Image from Mixed Noisy Data
International Journal of Computer Vision
Fixed-Point Continuation for $\ell_1$-Minimization: Methodology and Convergence
SIAM Journal on Optimization
Fuzzy peer groups for reducing mixed Gaussian-impulse noise from color images
IEEE Transactions on Image Processing
From Local Kernel to Nonlocal Multiple-Model Image Denoising
International Journal of Computer Vision
Mixed Gaussian and uniform impulse noise analysis using robust estimation for digital images
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Fast Two-Phase Image Deblurring Under Impulse Noise
Journal of Mathematical Imaging and Vision
Restoration of images corrupted by Gaussian and uniform impulsive noise
Pattern Recognition
An efficient two-phase L1-TV method for restoring blurred images with impulse noise
IEEE Transactions on Image Processing
Switching bilateral filter with a texture/noise detector for universal noise removal
IEEE Transactions on Image Processing
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Deterministic edge-preserving regularization in computed imaging
IEEE Transactions on Image Processing
Fast, robust total variation-based reconstruction of noisy, blurred images
IEEE Transactions on Image Processing
Noise adaptive soft-switching median filter
IEEE Transactions on Image Processing
Selective removal of impulse noise based on homogeneity level information
IEEE Transactions on Image Processing
Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
A New SURE Approach to Image Denoising: Interscale Orthonormal Wavelet Thresholding
IEEE Transactions on Image Processing
Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
IEEE Transactions on Image Processing
Majorization–Minimization Algorithms for Wavelet-Based Image Restoration
IEEE Transactions on Image Processing
Sparse Representation for Color Image Restoration
IEEE Transactions on Image Processing
Adaptive median filters: new algorithms and results
IEEE Transactions on Image Processing
Robust Video Restoration by Joint Sparse and Low Rank Matrix Approximation
SIAM Journal on Imaging Sciences
A restoration algorithm for images contaminated by mixed Gaussian plus random-valued impulse noise
Journal of Visual Communication and Image Representation
Total variation regularization algorithms for images corrupted with different noise models: a review
Journal of Electrical and Computer Engineering
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In this paper, we study the restoration of images corrupted by Gaussian plus impulse noise, and propose a l"1-l"0 minimization approach where the l"1 term is used for impulse denoising and the l"0 term is used for a sparse representation over certain unknown dictionary of images patches. The main algorithm contains three phases. The first phase is to identify the outlier candidates which are likely to be corrupted by impulse noise. The second phase is to recover the image via dictionary learning on the free-outlier pixels. Finally, an alternating minimization algorithm is employed to solve the proposed minimization energy function, leading to an enhanced restoration based on the recovered image in the second phase. Experimental results are reported to compare the existing methods and demonstrate that the proposed method is better than the other methods.