Asymptotic Linear Convergence of ADMM for Isotropic TV Norm Compressed Sensing
Abstract
Abstract We prove an explicit local linear rate for ADMM solving the isotropic Total Variation (TV) norm compressed sensing problem in multiple dimensions, by analyzing the auxiliary variable in the equivalent Douglas-Rachford splitting on a dual problem. Numerical verification on large 3D problems and real MRI data will be shown. The proven rate is not sharp, but it provides an explicit upper bound that appears close to the observed convergence rate in numerical experiments, although we do not claim this behavior holds in general.
Fields of Study & Subjects
Sparse and Compressive Sensing Techniques
Photoacoustic and Ultrasonic Imaging
Image and Signal Denoising Methods
Publication details
- Journal / source
- Journal of Optimization Theory and Applications
- Volume
- 210
- Issue
- 3
- Publication date
- 1 September 2026
- Language
- EN