Comparing different thresholding algorithms for segmenting auroras

Abstract

Extracting aurora oval boundary from spacecraft UV imagery is not a trivial problem. The distinction between aurora and background varies depending on the factors such as the date, time of the day, and satellite position. Thresholding technique is a well-known technique for detecting aurora boundary from satellite imagery. In this study, three distinct thresholding algorithms, mixture modeling, fuzzy sets and entropy thresholding were applied to a selected set of UV images measured on board Polar satellite to examine their effectiveness in aurora boundary detection. Two thresholding approaches were taken: global thresholding and adaptive thresholding. As expected, adaptive thresholding approach showed better results. In addition to these algorithms, another new algorithm (edge-based) was examined using adaptive approach. This thresholding algorithm detects aurora oval by identifying the boundary transition between aurora and background. The results from these different algorithms are presented.