Tag: synthetic aperture sonar

Abstract: Side-look synthetic aperture sonar (SAS) can produce very high quality images of the seabed. The imagery generated by SAS sensors display the seafloor and associated textures, such as sand ripples or seagrass. The characterization of SAS imagery is important for applications such as the detection and classification of targets, seabed segmentation and classification, and […]

Abstract: A boundary detection algorithm for synthetic aper- ture sonar (SAS) images that draws upon a popular superpixel formation algorithm is detailed and tested against a set of SAS images containing a variety of common seabed categories. Textural clues are gathered using a novel DP clustering algorithm that replaces the traditional K-means operator used in […]

Abstract: Side-look synthetic aperture sonar (SAS) can produce very high quality images of the sea-floor. The aim of this work is to develop a hierarchical Bayesian framework for estimating sand ripple characteristics from SAS imagery that can make use of multiple passes over an area at a variety of ranges. Using a hierarchical Bayesian framework […]

Abstract: In this paper we describe an unsupervised approach to seabed co-segmentation over the multiple sonar images collected in sonar surveys. We adapt a traditional single image segmentation texton-based approach to the sonar survey task by modifying the texture extraction filter bank to better model possible sonar image textures. Two different algorithms for building a […]