28 September 2016 Meteor tracking via local pattern clustering in spatio-temporal domain
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Abstract
Reliable meteor detection is one of the crucial disciplines in astronomy. A variety of imaging systems is used for meteor path reconstruction. The traditional approach is based on analysis of 2D image sequences obtained from a double station video observation system. Precise localization of meteor path is difficult due to atmospheric turbulence and other factors causing spatio-temporal fluctuations of the image background. The proposed technique performs non-linear preprocessing of image intensity using Box-Cox transform as recommended in our previous work. Both symmetric and asymmetric spatio-temporal differences are designed to be robust in the statistical sense. Resulting local patterns are processed by data whitening technique and obtained vectors are classified via cluster analysis and Self-Organized Map (SOM).
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Jaromír Kukal, Jaromír Kukal, Martin Klimt, Martin Klimt, Jan Švihlík, Jan Švihlík, Karel Fliegel, Karel Fliegel, } "Meteor tracking via local pattern clustering in spatio-temporal domain", Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99712M (28 September 2016); doi: 10.1117/12.2237649; https://doi.org/10.1117/12.2237649
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