ABSTRACT
Estimation of wavefront errors in three dimensions is required to mitigate isoplanatic errors when using adaptive optics or numerical restoration algorithms to recover high-resolution images from blurred data taken through atmospheric turbulence. Present techniques rely on multiple beacons, either natural stars or laser guide stars, to probe the atmospheric aberration along different lines of sight, followed by tomographic projection of the measurements. In this Letter, we show that a three-dimensional estimate of the wavefront aberration can be recovered from measurements by a single guide star in the case where the aberration is stratified, provided that the telescope tracks across the sky with nonuniform angular velocity. This is generally the case for observations of artificial Earth-orbiting satellites, and the new method is likely to find application in ground-based telescopes used for space situational awareness.
ABSTRACT
We demonstrate that high-resolution imaging through strong atmospheric turbulence can be achieved by acquiring data with a system that captures short exposure ("speckle") images using a range of aperture sizes and then using a bootstrap multi-frame blind deconvolution restoration process that starts with the smallest aperture data. Our results suggest a potential paradigm shift in how we image through atmospheric turbulence. No longer should image acquisition and post processing be treated as two independent processes: they should be considered as intimately related.
ABSTRACT
We describe a multiframe blind deconvolution (MFBD) algorithm that uses spectral ratios (the ratio of the Fourier spectra of two data frames) to model the inherent temporal signatures encoded by the observed images. In addition, by focusing on the separation of the object spectrum and system transfer functions only at spatial frequencies where the measured signal is above the noise level, we significantly reduce the number of unknowns to be determined. This "compact" MFBD yields high-quality restorations in a much shorter time than is achieved with MFBD algorithms that do not model the temporal signatures; it may also provide higher-fidelity solutions.
