When Too Similar Is Bad: A Practical Example of the Solar Dynamics Observatory Content-Based Image-Retrieval System

  • Juan M. BandaEmail author
  • Michael A. Schuh
  • Tim Wylie
  • Patrick McInerney
  • Rafal A. Angryk
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 241)


The measuring of interest and relevance have always been some of the main concerns when analyzing the results of a Content-Based Image-Retrieval (CBIR) system. In this work, we present a unique problem that the Solar Dynamics Observatory (SDO) CBIR system encounters: too many highly similar images. Producing over 70,000 images of the Sun per day, the problem of finding similar images is transformed into the problem of finding similar solar events based on image similarity. However, the most similar images of our dataset are temporal neighbors capturing the same event instance. Therefore a traditional CBIR system will return highly repetitive images rather than similar but distinct events. In this work we outline the problem in detail, present several approaches tested in order to solve this important image data mining and information retrieval issue.


Similar Image Solar Event Solar Dynamics Observatory Solar Image CBIR System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Juan M. Banda
    • 1
    Email author
  • Michael A. Schuh
    • 1
  • Tim Wylie
    • 1
  • Patrick McInerney
    • 1
  • Rafal A. Angryk
    • 1
  1. 1.Montana State UniversityBozemanUSA

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