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.
- Fast algorithm
- Subband adaptive
- Wavelet regularized inverse problem
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering