Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Diffusion-Inspired Shrinkage Functions and Stability Results for Wavelet Denoising
International Journal of Computer Vision
Wavelet-based signal de-noising via simple singularities approximation
Signal Processing
Image Denoising Via Learned Dictionaries and Sparse representation
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
Unsupervised patch-based image regularization and representation
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Wavelet footprints: theory, algorithms, and applications
IEEE Transactions on Signal Processing
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Variational approach for edge-preserving regularization using coupled PDEs
IEEE Transactions on Image Processing
Spatially adaptive wavelet thresholding with context modeling for image denoising
IEEE Transactions on Image Processing
A joint inter- and intrascale statistical model for Bayesian wavelet based image denoising
IEEE Transactions on Image Processing
A new iterated two-band diffusion equation: theory and its application
IEEE Transactions on Image Processing
Image denoising using scale mixtures of Gaussians in the wavelet domain
IEEE Transactions on Image Processing
Feature-based wavelet shrinkage algorithm for image denoising
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
A New SURE Approach to Image Denoising: Interscale Orthonormal Wavelet Thresholding
IEEE Transactions on Image Processing
Pointwise Shape-Adaptive DCT for High-Quality Denoising and Deblocking of Grayscale and Color Images
IEEE Transactions on Image Processing
Image Denoising Using Similarities in the Time-Scale Plane
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
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This paper exploits the time scale structure of the wavelet coefficients for implementing a novel and fast scheme for signal and image denoising. The time scale behavior of the coefficients is rigorously modeled through superposition of simple atoms using suitable projection spaces. This result allows us to avoid expensive numerical schemes requiring a low computational effort. Extensive experimental results show the competitive performances of the proposed approach.