Paper Info
Title
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
Year
DOI
Venue
2001
10.1109/ICIP.2001.959175
Image Processing, 2001. Proceedings. 2001 International Conference
Keywords
Field
DocType
astronomical techniques,astronomy computing,content-based retrieval,feature extraction,image recognition,image retrieval,image segmentation,image sequences,solar flares,visual databases,SolarSPIRE,Sun,Web-based interface,bright spots,content-based retrieval,dark spots,image sequence archives,query,relative intensity,satellite images,size time series,solar flares,spatio-temporal behavior,temporal solar imagery,temporally persistent objects
Computer vision,Satellite,Solar flare,Pattern recognition,Computer science,Image retrieval,Image segmentation,Feature extraction,Content based retrieval,Artificial intelligence,Image sequence
Conference
Volume
ISSN
ISBN
1
1522-4880
0-7803-6725-1
Citations 
PageRank 
References 
4
0.89
0
Authors
7
Name
Order
Citations
PageRank
Matthew Hill1545.42
Vittorio Castelli2928129.71
Chung-sheng Li31372222.33
Yuan-chi Chang437738.05
Lawrence D. Bergman566061.49
John R. Smith64939487.88
Barbara J. Thompson741.23