Comparing Different Thresholding Algorithms for Segmenting Auroras

  • Authors:

  • Xiang Li;Rahul Ramachandran;Matt He;Sunil Movva;John Rushing;Sara Graves;Wladislaw Lyatsky;Arjun Tan;Glynn Germany

  • Affiliations:

  • -;-;-;-;-;-;-;-;-

  • Venue:
  • ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
  • Year:
  • 2004

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Abstract

Extracting aurora oval boundary from spacecraftUV imagery is not a trivial problem. The distinctionbetween aurora and background varies depending onthe factors such as the date, time of the day, andsatellite position. Thresholding technique is a well-knowntechnique for detecting aurora boundary fromsatellite imagery. In this study, three distinctthresholding algorithms, Mixture Modeling, FuzzySets and Entropy thresholding were applied to aselected set of UV images measured on board Polarsatellite to examine their effectiveness in auroraboundary detection. Two thresholding approacheswere taken: global thresholding and adaptivethresholding. As expected, adaptive thresholdingapproach showed better results. In addition to thesealgorithms, another new algorithm (Edge-Based) wasexamined using adaptive approach. This thresholdingalgorithm detects aurora oval by identifying theboundary transition between aurora and background.The results from these different algorithms arepresented in this paper.