Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling
International Journal of Computer Vision
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Diffusions and Confusions in Signal and Image Processing
Journal of Mathematical Imaging and Vision
Adaptive Window Size Image De-noising Based on Intersection of Confidence Intervals (ICI) Rule
Journal of Mathematical Imaging and Vision
Edges as Outliers: Anisotropic Smoothing Using Local Image Statistics
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Epitomic analysis of appearance and shape
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Image Decomposition into a Bounded Variation Component and an Oscillating Component
Journal of Mathematical Imaging and Vision
Higher-Order Image Statistics for Unsupervised, Information-Theoretic, Adaptive, Image Filtering
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Fields of Experts: A Framework for Learning Image Priors
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Adaptive spatio-temporal restoration for 4d fluorescence microscopic imaging
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Curvature-Preserving regularization of multi-valued images using PDE's
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
The curvelet transform for image denoising
IEEE Transactions on Image Processing
On the origin of the bilateral filter and ways to improve it
IEEE Transactions on Image Processing
Image denoising using scale mixtures of Gaussians in the wavelet domain
IEEE Transactions on Image Processing
Region filling and object removal by exemplar-based image inpainting
IEEE Transactions on Image Processing
Image information restoration based on long-range correlation
IEEE Transactions on Circuits and Systems for Video Technology
Space-Time Adaptation for Patch-Based Image Sequence Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlocal Image and Movie Denoising
International Journal of Computer Vision
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
International Journal of Computer Vision
Patch-based video processing: a variational Bayesian approach
IEEE Transactions on Circuits and Systems for Video Technology
From Local Kernel to Nonlocal Multiple-Model Image Denoising
International Journal of Computer Vision
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
Image reconstruction using particle filters and multiple hypotheses testing
IEEE Transactions on Image Processing
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A novel adaptive and patch-based approach is proposed for image regularization and representation. The method is unsupervised and based on a pointwise selection of small image patches of fixed size in the variable neighborhood of each pixel. The main idea is to associate with each pixel the weighted sum of data points within an adaptive neighborhood and to use image patches to take into account complex spatial interactions in images. In this paper, we consider the problem of the adaptive neighborhood selection in a manner that it balances the accuracy of the estimator and the stochastic error, at each spatial position. Moreover, we propose a practical algorithm with no hidden parameter for image regularization that uses no library of image patches and no training algorithm. The method is applied to both artificially corrupted and real images and the performance is very close, and in some cases even surpasses, to that of the best published denoising methods.