Representing Images Using Nonorthogonal Haar-Like Bases
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Adaptivity to Variable Smoothness for Exemplar-Based Image Regularization and Representation
International Journal of Computer Vision
A Fast Scheme for Multiscale Signal Denoising
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Image Denoising Using Similarities in the Time-Scale Plane
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
International Journal of Computer Vision
Compressive sensing reconstruction with prior information by iteratively reweighted least-squares
IEEE Transactions on Signal Processing
Image sequence denoising via sparse and redundant representations
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Personal photo enhancement using example images
ACM Transactions on Graphics (TOG)
Bayesian non-local means filter, image redundancy and adaptive dictionaries for noise removal
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Non-local kernel regression for image and video restoration
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
A high-quality video denoising algorithm based on reliable motion estimation
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
A multichannel spatial compressed sensing approach for direction of arrival estimation
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
Using the higher order singular value decomposition for video denoising
EMMCVPR'11 Proceedings of the 8th international conference on Energy minimization methods in computer vision and pattern recognition
On single image scale-up using sparse-representations
Proceedings of the 7th international conference on Curves and Surfaces
Time-Scale Similarities for Robust Image De-noising
Journal of Mathematical Imaging and Vision
Evolution-enhanced multiscale overcomplete dictionaries learning for image denoising
Engineering Applications of Artificial Intelligence
A dictionary learning approach for classification: separating the particularity and the commonality
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
Computer-Aided reclamation of lost art
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
Dictionary learning and similarity regularization based image noise reduction
Journal of Visual Communication and Image Representation
Non-negative sparse decomposition based on constrained smoothed ℓ0 norm
Signal Processing
Unsupervised images segmentation via incremental dictionary learning based sparse representation
Information Sciences: an International Journal
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We address the image denoising problem, where zeromean white and homogeneous Gaussian additive noise should be removed from a given image. The approach taken is based on sparse and redundant representations over a trained dictionary. The proposed algorithm denoises the image, while simultaneously trainining a dictionary on its (corrupted) content using the K-SVD algorithm. As the dictionary training algorithm is limited in handling small image patches, we extend its deployment to arbitrary image sizes by defining a global image prior that forces sparsity over patches in every location in the image. We show how such Bayesian treatment leads to a simple and effective denoising algorithm, with state-of-the-art performance, equivalent and sometimes surpassing recently published leading alternative denoising methods.