|Stochastic Systems Group|
Automatic localization of curvi-linear features (boundaries), including oceanic fronts and contours of rings such as those associated with the free-jet portion of the Gulf Stream, is a challenging task, especially in the case of missing observations due to cloud cover. Having this as motivation, we explore whether techniques successfully used for non-oceanographic problems can be beneficial in the realm of oceanography. The goal is to apply a generalized version of the Mumford-Shah functional, a variational technique used in photographic and medical imaging applications, to an oceanographic problem. This method performs optimal smoothing jointly with localization of the feature boundaries. The feature boundary partitions the region into two or more subregions. In addition to locating the front, we estimate the field, which interpolates across areas of missing data, but properly maintains the discontinuity at the boundary. Optimal interpolation is commonly performed in data analysis and assimilation. However, the technique presented by us is distinctive in the sense that it incorporates information about the feature boundaries into the field estimation process.
We will briefly summarize the use of curve evolution, and the associated level set method, for our problem, and present experimental results of our technique on various satellite observations of SST data. Preliminary results show reasonable localization of a particular oceanic front (the Gulf Stream).
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