Abstract
A method for tracking ice floes in sequential satellite imagery is presented. The approach, based on probability distributions, directly incorporates the spatial information about feature locations into the estimation procedure. Given an image taken at time t/sub 0/, a probability model is used to determine how features in the image will appear at time t/sub 1/, and the probability distribution is used to identify features common to both images. The use of a probability model provides a means to measure the goodness of fit of the resulting matches. The features used are the outlines of sea ice floes observed in SAR (synthetic aperture radar) images, although the method can be applied to any set of features. The floe outlines are found using an erosion-propagation algorithm which combines erosion from mathematical morphology with local propagation of information about floe edges. >
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