A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
A note on the applied use of MDL approximations
Neural Computation
The Minimum Description Length Principle (Adaptive Computation and Machine Learning)
The Minimum Description Length Principle (Adaptive Computation and Machine Learning)
Information and Complexity in Statistical Modeling
Information and Complexity in Statistical Modeling
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
Minimum Description Length Denoising With Histogram Models
IEEE Transactions on Signal Processing
Filtering random noise from deterministic signals via datacompression
IEEE Transactions on Signal Processing
Fisher information and stochastic complexity
IEEE Transactions on Information Theory
Minimax description length for signal denoising and optimized representation
IEEE Transactions on Information Theory
Analysis of multiresolution image denoising schemes using generalized Gaussian and complexity priors
IEEE Transactions on Information Theory
Asymptotic minimax regret for data compression, gambling, and prediction
IEEE Transactions on Information Theory
Wavelet thresholding via MDL for natural images
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Strong optimality of the normalized ML models as universal codes and information in data
IEEE Transactions on Information Theory
Exact minimax strategies for predictive density estimation, data compression, and model selection
IEEE Transactions on Information Theory
Kolmogorov's structure functions and model selection
IEEE Transactions on Information Theory
The context-tree weighting method: basic properties
IEEE Transactions on Information Theory
Adaptive wavelet thresholding for image denoising and compression
IEEE Transactions on Image Processing
Complexity-regularized image denoising
IEEE Transactions on Image Processing
Image denoising using scale mixtures of Gaussians in the wavelet domain
IEEE Transactions on Image Processing
Wavelet filter evaluation for image compression
IEEE Transactions on Image Processing
MML Invariant Linear Regression
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
Model selection by sequentially normalized least squares
Journal of Multivariate Analysis
| Hi-index | 35.68 |
We refine and extend an earlier minimum description length (MDL) denoising criterion for wavelet-based denoising. We start by showing that the denoising problem can be reformulated as a clustering problem, where the goal is to obtain separate clusters for informative and noninformative wavelet coefficients, respectively. This suggests two refinements, adding a code-length for the model index, and extending the model in order to account for subband-dependent coefficient distributions. A third refinement is the derivation of soft thresholding inspired by pndictive universal coding with weighted mixtures. We propose a practical method incorporating all three refinements, which is shown to achieve good performance and robustness in denoising both artificial and natural signals.