Stripe segmentation of oceanic internal waves in synthetic aperture radar images based on Mask R-CNN

Abstract

The development of deep learning and remote sensing makes it possible to obtain information about oceanic internal waves from massive data. Oceanic internal waves play an important role in ocean activities. To obtain the light and dark stripes from synthetic aperture radar (SAR) images, a stripe segmentation algorithm for oceanic internal waves is proposed based on Mask R-CNN. The research results show that the proposed method can not only identify whether there are oceanic internal waves, but also obtain the respective locations of the light and dark stripes in the images. The width and the direction angle of each light and dark stripe can be obtained efficiently by a separation and matching method with the sector region (SMMSR). Moreover, based on the identified relative locations of the light and dark stripes, it is possible to further determine the time when the oceanic internal waves undergo polarity conversion.