ψ-s correlation and dynamic time warping: two methods for tracking ice floes in SAR images

In recent years, there has been an interest in automating the process of producing maps of the motion of ice floes from SAR images acquired a few days apart. A common approach is to correlate raw pixel values in order to find corresponding features in two images. The problem with this approach is that the search space is often prohibitive when ice floes rotate, as they frequently do. We present two algorithms for performing shape matching on ice floe boundaries in SAR images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the $-s curve. The first algorithm uses normalized correlation to match the $-s curves, while the second uses dynamic programming to compute a n elastic match that better accommodates ice floe deformation.