Unsupervised, Information-Theoretic, Adaptive Image Filtering for Image Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multivariate Statistical Models for Image Denoising in the Wavelet Domain
International Journal of Computer Vision
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
Robust Estimation Approach for NL-Means Filter
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Fast Prototype Based Noise Reduction
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Iterative weighted maximum likelihood denoising with probabilistic patch-based weights
IEEE Transactions on Image Processing
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
Markovian clustering for the non-local means image denoising
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Generalised Nonlocal Image Smoothing
International Journal of Computer Vision
Nonlocal-means image denoising technique using robust M-estimator
Journal of Computer Science and Technology
A Variational Framework for Exemplar-Based Image Inpainting
International Journal of Computer Vision
MRI tissue classification with neighborhood statistics: a nonparametric, entropy-minimizing approach
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Total Variation as a Local Filter
SIAM Journal on Imaging Sciences
Unsupervised patch-based image regularization and representation
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Nonparametric neighborhood statistics for MRI denoising
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
An MMSE approach to nonlocal image denoising: Theory and practical implementation
Journal of Visual Communication and Image Representation
Benford's law for natural and synthetic images
Computational Aesthetics'05 Proceedings of the First Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
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The restoration of images is an important and widely studied problem in computer vision and image processing. Various image filtering strategies have been effective, but invariably make strong assumptions about the properties of the signal and/or degradation. Therefore, these methods typically lack the generality to be easily applied to new applications or diverse image collections. This paper describes a novel unsupervised, information-theoretic, adaptive filter (UINTA) that improves the predictability of pixel intensities from their neighborhoods by decreasing the joint entropy between them. Thus UINTA automatically discovers the statistical properties of the signal and can thereby restore a wide spectrum of images and applications. This paper describes the formulation required to minimize the joint entropy measure, presents several important practical considerations in estimating image-region statistics, and then presents results on both real and synthetic data.