Multiscale edge approach for the detection and location of internal waves from SAR images

In this paper, an efficient computational framework for the extraction of mesoscale features, i.e. internal waves, present in SAR images is discussed. The first problem in a mesoscale detection system is to distinguish sea from land in the SAR imagery. A method for coastline detection based on a sequence of basic processing procedures followed by a contour tracing algorithm is introduced in order to obtain sea-land separation to enhance the internal wave detection problem. The utility of wavelet analysis as a tool for automatic oceanic internal wave detection and location from SAR images is then examined using the 2-D wavelet transform based on the multiscale gradient detection method. We show that the evolution of local maxima of the wavelet transform across scales characterize the local shape of these quasi-linear periodic structures. The results from this study show that wavelet analysis is an excellent tool to detect and locate internal wave features from satellite images against internal wave look-alikes.