Super-resolution via superset selection and pruning
Information Theory
2013-06-11 v2 math.IT
Numerical Analysis
Abstract
We present a pursuit-like algorithm that we call the "superset method" for recovery of sparse vectors from consecutive Fourier measurements in the super-resolution regime. The algorithm has a subspace identification step that hinges on the translation invariance of the Fourier transform, followed by a removal step to estimate the solution's support. The superset method is always successful in the noiseless regime (unlike L1-minimization) and generalizes to higher dimensions (unlike the matrix pencil method). Relative robustness to noise is demonstrated numerically.
Cite
@article{arxiv.1302.6288,
title = {Super-resolution via superset selection and pruning},
author = {Laurent Demanet and Deanna Needell and Nam Nguyen},
journal= {arXiv preprint arXiv:1302.6288},
year = {2013}
}