Auroral Feature Detection by combined Image Segmentation and Clustering Analysis

Details Auroral Feature Detection by combined Image Segmentation and Clustering Analysis Auroral Feature Detection by combined Image Segmentation and Clustering Analysis

Dec 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agufmsm41a1689g&link_type=abstract

American Geophysical Union, Fall Meeting 2009, abstract #SM41A-1689

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[0540] Computational Geophysics / Image Processing, [2704] Magnetospheric Physics / Auroral Phenomena, [3252] Mathematical Geophysics / Spatial Analysis, [6220] Planetary Sciences: Solar System Objects / Jupiter

Scientific paper

We extend our work on image segmentation (VOISE algorithm, Guio and Achilleos 2009, MNRAS) where we used VOISE to construct segmentation maps of auroral images from the Jovian polar regions. In this paper we transform such segmentation maps to a system of magnetic latitude and longitude. This transformation makes use of an eccentric dipole representation of the Jovian internal magnetic field that corresponds to the coefficients of the VIP4 model (Connerney et al 1998, JGR). We comment on the efficiency and reliability of this approach for enabling the characterisation of arc-like features, approximately aligned along contours of constant magnetic latitude, and regions linked to the polar cap and the cusp. We also comment on the role of the `coherence' of data in detection of features near the background levels.

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