Physics
Scientific paper
Dec 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005agufmsm51b1285c&link_type=abstract
American Geophysical Union, Fall Meeting 2005, abstract #SM51B-1285
Physics
2407 Auroral Ionosphere (2704), 2704 Auroral Phenomena (2407)
Scientific paper
A new shape-based method for segmenting the auroral oval from NASA POLAR Ultraviolet Imager (UVI) data is presented. The POLAR mission has produced millions of UVI images, making automated auroral segmentation a beneficial and critical early processing step in analysis of high-latitude ionosphere-thermopshere-magnetosphere (ITM) coupling using auroral images. Past approaches to automatically or semi-automatically segment the auroral oval from UVI imagery include various types of thresholding, histogram-based K-means, and neural network methods. The existing approaches are generally not robust due to the high noise level, the low level of intensity contrast, and the day glow present in some UVI images. A common shortcoming of existing methods is incomplete detection of the auroral oval for some images. In some cases, existing methods can even fail to detect any part of the oval. The method introduced here is more robust to the challenges of the UVI imagery. Recently, we have demonstrated that the auroral oval's shape in UVI images is well-modelled as an elliptic arc. The segmentation method introduced here exploits this finding; we allow shape knowledge to guide auroral processing. The method involves use of a linear least-squares based shape parameter binning approach that operates on pixels determined from an image-specific thresholding step. The binning approach utilizes a modified randomized Hough Transform scheme that is also fast (faster than conventional binning schemes). The approach treats the inner and outer auroral oval boundaries separately and also incorporates heuristics that allow robust differentiation of appropriate inner and outer boundaries. The new method has been tested on more than 1000 aurora images. Results indicate that the method is highly reliable, even in the presence of high image noise, low contrast, and moderate levels of day glow.
Cao Chen
Germany G. G.
Newman Timothy S.
No associations
LandOfFree
A Shape-Based Technique for Aurora Oval Segmentation From UVI Images does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with A Shape-Based Technique for Aurora Oval Segmentation From UVI Images, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Shape-Based Technique for Aurora Oval Segmentation From UVI Images will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1028528