Image Quality in High-resolution and High-cadence Solar Imaging

TL;DR

This paper evaluates high-cadence solar imaging techniques, demonstrating that data rates above 50 Hz improve image restoration quality, with implications for designing future high-resolution solar observation sequences.

Contribution

It introduces a detailed analysis of image quality metrics and optimal data acquisition rates for high-cadence solar imaging, combining speckle masking and adaptive optics.

Findings

High-cadence imaging (>50 Hz) enhances image restoration performance.

MFGS metric remains effective despite structure-dependent modifications.

Millisecond exposures are insufficient to reach daytime seeing coherence time.

Abstract

Broad-band imaging and even imaging with a moderate bandpass (about 1 nm) provides a "photon-rich" environment, where frame selection ("lucky imaging") becomes a helpful tool in image restoration allowing us to perform a cost-benefit analysis on how to design observing sequences for high-spatial resolution imaging in combination with real-time correction provided by an adaptive optics (AO) system. This study presents high-cadence (160 Hz) G-band and blue continuum image sequences obtained with the High-resolution Fast Imager (HiFI) at the 1.5-meter GREGOR solar telescope, where the speckle masking technique is used to restore images with nearly diffraction-limited resolution. HiFI employs two synchronized large-format and high-cadence sCMOS detectors. The Median Filter Gradient Similarity (MFGS) image quality metric is applied, among others, to AO-corrected image sequences of a pore and a small sunspot observed on 2017 June 4 and 5. A small region-of-interest, which was selected for fast imaging performance, covered these contrast-rich features and their neighborhood, which were part of active region NOAA 12661. Modifications of the MFGS algorithm uncover the field- and structure-dependency of this image quality metric. However, MFGS still remains a good choice for determining image quality without a priori knowledge, which is an important characteristic when classifying the huge number of high-resolution images contained in data archives. In addition, this investigation demonstrates that a fast cadence and millisecond exposure times are still insufficient to reach the coherence time of daytime seeing. Nonetheless, the analysis shows that data acquisition rates exceeding 50 Hz are required to capture a substantial fraction of the best seeing moments, significantly boosting the performance of post-facto image restoration.