@article{DenkerDinevaBalthasaretal.2018,
  author    = {Denker, Carsten and Dineva, Ekaterina Ivanova and Balthasar, Horst and Verma, Meetu and Kuckein, Christoph and Diercke, Andrea and Manrique Gonzalez, Sergio Javier Gonzalez},
  title     = {Image Quality in High-resolution and High-cadence Solar Imaging},
  series = {Solar physics : a journal for solar and solar-stellar research and the study of solar terrestrial physics},
  volume    = {293},
  journal   = {Solar physics : a journal for solar and solar-stellar research and the study of solar terrestrial physics},
  number    = {3},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {0038-0938},
  doi       = {10.1007/s11207-018-1261-1},
  pages     = {24},
  year      = {2018},
  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 imaging with high spatial resolution 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. The 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 contrastrich features and their neighborhood, which were part of Active Region NOAA 12661. Modifications of theMFGS algorithm uncover the field-and structure-dependency of this imagequality 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.},
  language  = {en}
}