Finding water depths from synthetic remotely sensed images

Mathematical morphology coupled with creation of a time stack image and principal oscillation pattern analysis are used to determine the water depths over a known sloping bottom from synthetic remotely sensed images. The data, produced by a simulator, consisted of 60 images, each 256/spl times/256 pixels, separated by 1 second in time. The mathematical depth results are compared with those derived using principal oscillation pattern analysis by which three significant complex pairs of patterns are found with their corresponding characteristic times: e-folding times and periods. From these results and by using the classical hydrodynamic theory of gravity waves, water depths are determined. Both analyses yield small errors for the simulated data, indicating both methods should perform reliably for real data.