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Session 12 - Image Processing.
Oral session, Monday, June 30
Ballroom A, Chair: Stephen Kahler
Various features in solar images observed at different wavelengths are used to monitor and forecast solar activity. Many of these features are currently traced manually to provide composite images of features observed in these different images. The NOAA/Space Environment Center has been working on algorithms to automatically extract these features from images received at our Space Weather Operations Branch for routine solar patrol. Algorithms for preprocessing these images (including flat field corrections derived from the image itself) and for extracting large-scale magnetic inversion lines are currently being beta tested for real-time operations. Algorithms for filament recognition and sunspot recognition and classification are being tested and modified for real-time operations. In the next few years we will be extending these feature-recognition techniques to prepare for the rapid influx of solar x-ray image data (one per minute) from the GOES Solar X-ray Imagers (SXI). Our goal is to automatically alert the forecasters of significant solar changes, provide a composite overview drawing of solar features, and develop a database of feature properties derived with a standard processing algorithm. Derived feature properties will then be used to provide the statistical guidance on the correlations among solar-terrestrial phenomena of interest to the solar-terrestrial community of researchers and operators.
Program listing for Monday