A Curated Image Parameter Data Set from the Solar Dynamics Observatory Mission

Abstract

Abstract We provide a large image parameter data set extracted from the Solar Dynamics Observatory (SDO) mission’s Atmospheric Imaging Assembly (AIA) instrument, for the period of 2011 January through the current date, with the cadence of 6 minutes, for nine wavelength channels. The volume of the data set for each year is just short of 1 TiB. Toward achieving better results in the region classification of active regions and coronal holes, we improve on the performance of a set of 10 image parameters, through an in-depth evaluation of various assumptions that are necessary for calculation of these image parameters. Then, where possible, a method for finding an appropriate setting for the parameter calculations was devised, as well as a validation task to show our improved results. In addition, we include comparisons of JP2 and FITS image formats using supervised classification models, by tuning the parameters specific to the format of the images from which they are extracted and specific to each wavelength. The results of these comparisons show that utilizing JP2 images, which are significantly smaller files, is not detrimental to the region classification task that these parameters were originally intended for. Finally, we compute the tuned parameters on the AIA images and provide a public API (see http://dmlab.cs.gsu.edu/dmlabapi/) to access the data set. This data set can be used in a range of studies on AIA images, such as content-based image retrieval or tracking of solar events, where dimensionality reduction on the images is necessary for feasibility of the tasks.