Motion Estimation Techniques to Automatically Track Oceanographic Thermal Structures in Multisensor Image Sequences

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The ocean involves a complex set of physical, chemical, biological, and geological processes, interacting with each other to influence our climate and natural environment. One of the most important disciplines in oceanography is the study of the ocean dynamics and, particularly, the ocean surface circulation. One can estimate this by the automated tracking of thermal infrared features in pairs of sequential satellite imagery. In this context, an extensive analysis of different motion estimation techniques has been performed by employing databases with synthetic sequences, real sequences, and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">situ</i> measurements. Four region- based metrics and two differential algorithms are proposed to estimate surface currents in multitemporal and multisensor AVHRR and MODIS image sequences. Once the appropriate motion estimation techniques have been selected, a new methodology to compute ocean currents is proposed. It includes a preliminary step to precisely segment the oceanographic structures and a second step to track its motion using additional modules (initialization, preprocessing, and postprocessing) to increase effectiveness. The information provided by the segmentation step reduces computing times, initializes the motion estimation parameters with appropriate values, and increases the overall performance. In summary, this two-stage approach combines image processing tools and physical oceanography knowledge to achieve a good ocean current estimation.