Coronal mass ejections, which are explosions of solar material and energy into space, pose a potential threat to satellite and electrical grid infrastructures, yet little is known about the solar corona. Various questions exist, relating to the origins of these mass ejections as well as the mecha... Show moreCoronal mass ejections, which are explosions of solar material and energy into space, pose a potential threat to satellite and electrical grid infrastructures, yet little is known about the solar corona. Various questions exist, relating to the origins of these mass ejections as well as the mechanisms involved in coronal heating. The corona and coronal mass ejections are measured by satellite and ground-based coronagraphs, instruments that produce a false eclipse of the Sun in order to separate the extremely faint coronal signature from the bright solar disk. Earth’s atmosphere and the presence of aerosols limit the usefulness of images obtained from ground-based coronagraphs compared to satellite observations. We have developed image processing algorithms to remove aerosols from a new high-speed detector in real time. Two images, a mean and a median image, were first generated from a time series of images containing real aerosols. Then a thresholding algorithm was applied to all of the images within the time series. If the pixel values exceeded the mean and/or median image value, they were replaced with the value in that mean or median image. Both techniques were successful in removing aerosols from imagery. Due to signal-to-noise advantages gained by utilizing the mean image instead of the median image, the mean is the preferred method. Processing ∼1 second of imagery (150 frames per second) required ∼180 seconds on a dual-core 2.33 GHz CPU. Further optimization will promote real-time aerosol removal in solar observation. Show less
