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59th International Astronautical Congress
Glasgow, Scotland, 29 September - 3 October 2008

Automatic GEO Object Detection Algorithms
and their Implementation in the Framework
of the Apex II Image Processing System

Vladimir Kouprianov

Central (Pulkovo) Astronomical Observatory
of the Russian Academy of Sciences
Saint Petersburg, Russia

Large Field of View Survey Cameras

  • Efficient, but
  • Produce large amount of data (both orbital objects and field stars)

Typical Large-FOV Image

  • Overcrowded with star trails
  • Several dozens GEO objects are hard to detect
  • Need to obtain maximum information from a single image

Optical Aberrations

Star trail (image center) Star trail (image corner)

Apex II Software Package for Image Processing

  • General-purpose open-source astronomical image processing platform
  • Modern technologies – Python (flexible scripting programming language), packages for scientific computations and graphics, easily extendable modular structure
  • Used by more than 20 teams participating in and cooperating with ISON

Residual Image After Star Trail Subtraction

  • Complete elimination of star trails would take a lot of CPU time
  • Impossible due to distortion of trails by optics and atmosphere

Object Detection: Binary Image

  • Residual image still contains much more star trails than GEO objects; how to eliminate them?

Binary Image Filtering for Star Trail Elimination

Filtered Binary Image

  • Almost no star trail remains left
  • Remaining spurious detections are easily removed by comparing adjacent frames


  • Automatic processing of images taken by wide-field survey cameras require efficient algorithms for star trail elimination
  • Such an algorithm, based on logical filtering of a binary image, is proposed and implemented in the framework of the Apex II image processing system
  • 2 октября 2008
    Материалы докладов публикуются с согласия авторов

    Главная Новости ПулКОН РСДБ Обсерватории Публикации About us Контакт

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