Ghost Removal from Forward-Scan Sonar Views near the Sea Surface for Image Enhancement and 3-D Object Modeling

Abstract

Underwater sonar is the primary remote sensing and imaging modality within turbid environments with poor visibility. The two-dimensional (2-D) images of a target near the air–sea interface (or resting on a hard seabed), acquired by forward-scan sonar (FSS), are generally corrupted by the ghost and sometimes mirror components, formed by the multipath propagation of transmitted acoustic beams. In the processing of the 2-D FSS views to generate an accurate three-dimensional (3-D) object model, the corrupted regions have to be discarded. The sonar tilt angle and distance from the sea surface are two important parameters for the accurate localization of the ghost and mirror components. We propose a unified optimization technique for improving both the measurements of these two parameters from inexpensive sensors and the accuracy of a 3-D object model using 2-D FSS images at known poses. The solution is obtained by the recursive updating of sonar parameters and 3-D object model. Utilizing the 3-D object model, we can enhance the original images and generate synthetic views for arbitrary sonar poses. We demonstrate the performance of our method in experiments with the synthetic and real images of three targets: two dominantly convex coral rocks and a highly concave toy wood table.