Unified Convex Optimization Approach to Super-Resolution Based on Localized Kernels
arXiv:1501.01825
Abstract
The problem of resolving the fine details of a signal from its coarse scale measurements or, as it is commonly referred to in the literature, the super-resolution problem arises naturally in engineering and physics in a variety of settings. We suggest a unified convex optimization approach for super-resolution. The key is the construction of an interpolating polynomial based on localized kernels. We also show that the localized kernels act as the connecting thread to another wide-spread problem of stream of pulses.
References in corpus (6)
- Support detection in super-resolution
- MUSIC for Single-Snapshot Spectral Estimation: Stability and Super-resolution
- Super-resolution, Extremal Functions and the Condition Number of Vandermonde Matrices
- Super-Resolution Radar
- Super-Resolution from Short-Time Fourier Transform Measurements
- Non-uniform spline recovery from small degree polynomial approximation