Sonar-parameterized, continuous, localized basis function splatting for sonar image synthesis

A method of generating an azimuth-streaked sonar image representing a scene, comprising:

• obtaining a set of multi-dimensional continuous localized basis functions used to represent a scene;
• generating an initial sonar image based on rasterizing the scene into for a given pose;
• determining an azimuth streak probability image based on the set of multi-dimensional continuous localized basis functions for the given pose;
• determining azimuth streak receiver gain data based on the azimuth streak probability image;
• and
• generating an azimuth-streaked sonar image for the given pose based on the azimuth streak receiver gain data and the initial sonar image.

A method of generating a sonar image for a given pose through splatting continuous, localized radial basis functions, comprising:

• obtaining a set of multi-dimensional continuous localized basis functions used to represent a scene, wherein each multi-dimensional continuous localized basis functions of the set of multi-dimensional continuous localized basis functions is parameterized with a plurality of acoustic parameters including an acoustic target parameter;
• generating an initial sonar image of the scene for a given pose based on splatting at least one acoustic parameter other than the acoustic target parameter according to the given pose;
• generating an acoustic target parameterized image for the given pose based on splatting the acoustic target parameter of the set of multi-dimensional continuous localized basis functions according to the given pose;
• and
• generating a sonar image for the given pose based on the initial sonar image for the given pose and the acoustic target parameterized image for the given pose.

A method of de-streaking a sonar image, comprising:

• obtaining a set of multi-dimensional continuous localized basis functions used to represent a scene, wherein each multi-dimensional continuous localized basis functions of the set of multi-dimensional continuous localized basis functions is parameterized with at least one acoustic parameter;
• obtaining training data having at least one training data entry comprised of an azimuth-streaked sonar image for a given pose and a ground truth sonar image for the given pose,
• learning a set of azimuth-streak probability parameters for the using machine learning performed based on the training data;
• obtaining a subject sonar image;
• determining azimuth streak receiver gain data for the subject sonar image based on the learned set of azimuth-streak probability parameters;
• and
• generating an azimuth-destreaked image based on the azimuth streak receiver gain data and the learned set of azimuth-streak probability parameters.