A two-stage method for segmenting and estimating the motion of ionospheric electron density enhancements is presented. These enhancements occur during geomagnetic storms, when matter ejected from the sun enters the upper atmosphere. The first stage of the proposed method segments the enhancements in the images by using a tuned attribute morphology filter, based on feature contrast. A temporal feedback mechanism is also employed to improve the temporal stability of the outputs. The second stage makes use of shape contexts to calculate boundary matches. These matches are then used to estimate motion vectors and a post filter is applied to detect and correct anomalous vectors. Overall, the scheme produces data-driven estimates of the motion of ionospheric electron density enhancements that can be used to study the evolution of ionospheric storms. Illustrative results are presented for a sequence of images from the Halloween storm of 2003. The results of this technique can also be used to validate models and data from other instrumentation which images the ionosphere during storms.
|Proceedings of SPIE
|The International Society for Optical Engineering