Computer Vision for the Solar Dynamics Observatory (SDO)

Abstract

In Fall 2008 NASA selected a large international consortium to produce a comprehensive automated feature-recognition system for the Solar Dynamics Observatory (SDO). The SDO data that we consider are all of the Atmospheric Imaging Assembly (AIA) images plus surface magnetic-field images from the Helioseismic and Magnetic Imager (HMI). We produce robust, very efficient, professionally coded software modules that can keep up with the SDO data stream and detect, trace, and analyze numerous phenomena, inThe Solar Dynamics Observatory P.C.H. Martens et al.cluding flares, sigmoids, filaments, coronal dimmings, polarity inversion lines, sunspots, Xray bright points, active regions, coronal holes, EIT waves, coronal mass ejections (CMEs), coronal oscillations, and jets. We also track the emergence and evolution of magnetic elements down to the smallest detectable features and will provide at least four full-disk, nonlinear, force-free magnetic field extrapolations per day. The detection of CMEs and filaments is accomplished with Solar and Heliospheric Observatory (SOHO)/Large Angle and Spectrometric Coronagraph (LASCO) and ground-based Hα data, respectively. A completely new software element is a trainable feature-detection module based on a generalized imageclassification algorithm. Such a trainable module can be used to find features that have not yet been discovered (as, for example, sigmoids were in the pre-Yohkoh era). Our codes will produce entries in the Heliophysics Events Knowledgebase (HEK) as well as produce complete catalogs for results that are too numerous for inclusion in the HEK, such as the X-ray bright-point metadata. This will permit users to locate data on individual events as well as carry out statistical studies on large numbers of events, using the interface provided by the Virtual Solar Observatory. The operations concept for our computer vision system is that the data will be analyzed in near real time as soon as they arrive at the SDO Joint Science Operations Center and have undergone basic processing. This will allow the system to produce timely space-weather alerts and to guide the selection and production of quicklook images and movies, in addition to its prime mission of enabling solar science. We briefly describe the complex and unique data-processing pipeline, consisting of the hardware and control software required to handle the SDO data stream and accommodate the computer-vision modules, which has been set up at the Lockheed-Martin Space Astrophysics Laboratory (LMSAL), with an identical copy at the Smithsonian Astrophysical Observatory (SAO).

Three-Year Global Survey of Coronal Null Points from Potential-Field-Source-Surface (PFSS) Modeling and Solar Dynamics Observatory (SDO) Observations

“…The intent of future work is to also explore the separatrix surfaces associated with the observed CNPs found in our survey. This work can also be useful in future efforts to mine AIA data for additional CNPs, as shown by Martens et al (2012), and to investigate their temporal evolution. There are still many questions that need to be addressed: Why do some of the null points remain stable for so long while others quietly disappear?…”

Multi-Scale Gaussian Normalization for Solar Image Processing

“…Martens et al, 2012), most scientific works begin from visual inspection of images. In particular, the volume of data provided by AIA/SDO is so high that low-resolution images are often used as a starting point to find features of interest.…”

The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: SHARPs – Space-Weather HMI Active Region Patches

“…The HEK is a web-based tool designed to aid researchers in finding features and events of interest. Various features extracted or extrapolated from HMI data, such as the location of sunspots, polarity-inversion lines, and nonlinear force-free numerical models, are already available in the HEK (see Sections 13 -15 of Martens et al, 2012).…”