Solarspire: Querying temporal solar imagery by content

Abstract

In this paper, we describe a novel content-based retrieval application which permits astrophysicists to search large image sequence archives for solar phenomenon, such as solar flares, based on the spatio-temporal behavior of the solar phenomenon. Specifically, images are preprocessed to identify bright and dark spots based on their relative intensity with respect to their neighboring regions. Temporally persistent objects are then extracted from the collection of spots, and their spatio-temporal behavior represented as intensity and size time series. Users define a query in terms of a model of spatio-temporal behaviors through a web-based interface. The stored intensity and size time series are searched, and series segments that match the specified specified spatio-temporal behavior are returned. The benchmark results based on 2500 satellite images show that the proposed methodology demonstrated better than 85% accuracy on a solar phenomenon previously identified by astrophysicists.