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
Image Processing: The Fundamentals
Image Processing: The Fundamentals
Digital Image Processing
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A Variational Approach to Remove Outliers and Impulse Noise
Journal of Mathematical Imaging and Vision
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A New Efficient Impulse Detection Algorithm for the Removal of Impulse Noise
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing
Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing
Sparsity-based image denoising via dictionary learning and structural clustering
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
An augmented Lagrangian approach to general dictionary learning for image denoising
Journal of Visual Communication and Image Representation
Greed is good: algorithmic results for sparse approximation
IEEE Transactions on Information Theory
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization
IEEE Transactions on Image Processing
A universal noise removal algorithm with an impulse detector
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
A Detection Statistic for Random-Valued Impulse Noise
IEEE Transactions on Image Processing
Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
IEEE Transactions on Image Processing
Sparse Representation for Color Image Restoration
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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In this paper, we study the problem of restoring the image corrupted by additive Gaussian noise plus random-valued impulse noise. A novel noise classifier is firstly created to identify different noise in the corrupted image. Then, we use the remaining effective information to train an adaptive overcomplete dictionary for sparse representation of image patches with the help of masked K-SVD algorithm. Because of the adaptive nature of the learned dictionary, it can represent the image patches in concern more efficiently. Then, we minimize a variational model containing an optional data-fidelity term and a smooth regularization term respecting sparse representation of every image patch to get the final restored image. Extensive experimental results prove that our method cannot only remove noise from the corrupted image well, but also preserve more details and textures. It surpasses some state-of-the-art methods.