Matrix analysis
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
Multirate systems and filter banks
Multirate systems and filter banks
Iterative solution of nonlinear equations in several variables
Iterative solution of nonlinear equations in several variables
A generalized conditional gradient method and its connection to an iterative shrinkage method
Computational Optimization and Applications
Sparse reconstruction by separable approximation
IEEE Transactions on Signal Processing
Fixed-Point Continuation for $\ell_1$-Minimization: Methodology and Convergence
SIAM Journal on Optimization
A fast multilevel algorithm for wavelet-regularized image restoration
IEEE Transactions on Image Processing
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
SIAM Journal on Imaging Sciences
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
SIAM Journal on Imaging Sciences
Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency
IEEE Transactions on Signal Processing
Analysis of multiresolution image denoising schemes using generalized Gaussian and complexity priors
IEEE Transactions on Information Theory
Why Simple Shrinkage Is Still Relevant for Redundant Representations?
IEEE Transactions on Information Theory
An EM algorithm for wavelet-based image restoration
IEEE Transactions on Image Processing
Majorization–Minimization Algorithms for Wavelet-Based Image Restoration
IEEE Transactions on Image Processing
A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for Image Restoration
IEEE Transactions on Image Processing
A Fast Thresholded Landweber Algorithm for Wavelet-Regularized Multidimensional Deconvolution
IEEE Transactions on Image Processing
Hi-index | 35.68 |
We investigate a subband adaptive version of the popular iterative shrinkage/thresholding algorithm that takes different update steps and thresholds for each subband. In particular, we provide a condition that ensures convergence and discuss why making the algorithm subband adaptive accelerates the convergence. We also give an algorithm to select appropriate update steps and thresholds for when the distortion operator is linear and time invariant. The results in this paper may be regarded as extensions of the recent work by Vonesch and Unser.