Measurement of Sea Surface Characteristics from Radar Images Using Gradient Methods

Introduction. Remote sensing and monitoring of the sea surface are of great importance in such fields, as operational oceanography, environmental monitoring, etc. The ability to quickly assess the state of the sea surface is particularly relevant in areas that pose a danger to shipping, where rapid and accurate response becomes critical. Modern radars represent information as digital image series largely reminiscent to a frame series in a video stream, thus enabling the use of gradient methods originally designed for and proven successful in video analysis.

Aim. Determination of sea wave characteristics from radar images using gradient motion estimation methods. The use of gradient methods will allow implementing additional tools for processing radar image series obtained from sea backscatter.

Materials and methods. To assess the characteristics of the sea surface from radar images, gradient methods were used. To train the methods, a series of synthetic images of the sea surface obtained by mathematical modeling were used. To evaluate the effectiveness of the gradient methods, two representative experimental radar image series provided by the Institute of Oceanography RAS were employed.

Results. Using gradient methods, the direction and speed of waves were calculated from several consecutive radar observations. Regression models of the dependence of calculated values on the specified ones were constructed. The Farneback and TV-L1 methods proved to be effective especially for obtaining the direction of the sea waves.

Conclusion. An algorithm for evaluating speed and direction of the sea surface displacement using gradient methods was pre-trained using simulated model data. The implemented methods and algorithms for assessing the speed and direction of sea waves were validated using two experimental image series obtained from shipborne navigational radars.

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