MSIS sonar image segmentation method based on underwater viewshed analysis and high-density seabed model

High resolution images of Mechanically Scanned Imaging Sonars can bring detailed representation of underwater area if favorable conditions for acoustic signal to propagate are provided. However to properly asses underwater situation based solely on such data can be challenging for less than proficient interpreter. In this paper we propose a method to enhance interpretative potential of MSIS image by dividing it in to subareas depending on information about slope gradient and direction derived from high-density bathymetric model using viewshed analysis. Additional image channel is created to store data on adherence of sonar data into each class representing different information related to sea bed shape. The paper also contains details on segmentation algorithm using traditional image processing method.