Images of astronomical objects are distorted by the turbulence in Earth’s atmosphere. Deconvolution from Wavefront Sensing (DWFS) is a computer post-processing technique used by astronomers to reduce the effects of the atmosphere from images collected by ground-based telescopes. This paper investigates the relative performance of DWFS from two Wavefront Sensors (WFS), the curvature and geometric, used to estimate the aberrations introduced to the optical path by the turbulence. DWFS is performed using both the Wiener filter and the Lucy-Richardson algorithm. Our results show the geometric WFS has superior performance over the curvature WFS in both simulation and on-sky.
Paper
Full text
Image Correction with Curvature and Geometric Wavefront Sensors in Simulation and On-sky
Semantic Scholar · Physics · 2019
Abstract
Images of astronomical objects are distorted by the turbulence in Earth’s atmosphere. Deconvolution from Wavefront Sensing (DWFS) is a computer post-processing technique used by astronomers to reduce the effects of the atmosphere from images collected by ground-based telescopes. This paper investigates the relative performance of DWFS from two Wavefront Sensors (WFS), the curvature and geometric, used to estimate the aberrations introduced to the optical path by the turbulence. DWFS is performed using both the Wiener filter and the Lucy-Richardson algorithm. Our results show the geometric WFS has superior performance over the curvature WFS in both simulation and on-sky.