🤖 AI Summary
Circular synthetic aperture sonar (CSAS) enhances azimuth resolution and coverage but sacrifices seafloor shadow information—critical for target recognition and 3D reconstruction—due to its omnidirectional imaging. This work presents the first systematic approach to recover and exploit shadows from CSAS data: multi-view images are generated via sub-aperture filtering, clear shadows are extracted using a fixed-focus shadow enhancement (FFSE) technique, and an interactive visualization interface facilitates manual segmentation. Subsequently, a space-carving method infers the 3D shape of targets from shadow contours. By moving beyond the conventional reliance on intensity-only CSAS imagery, the proposed framework significantly improves target identification and demonstrates the efficacy and potential of shadow information for underwater 3D reconstruction.
📝 Abstract
Circular Synthetic Aperture Sonar (CSAS) provides a 360{\deg} azimuth view of the seabed, surpassing the limited aperture and mono-view image of conventional side-scan SAS. This makes CSAS a valuable tool for target recognition in mine warfare where the diversity of point of view is essential for reducing false alarms. CSAS processing typically produces a very high-resolution two-dimensional image. However, the parallax introduced by the circular displacement of the illuminator fill-in the shadow regions, and the shadow cast by an object on the seafloor is lost in favor of azimuth coverage and resolution. Yet the shadows provide complementary information on target shape useful for target recognition. In this paper, we explore a way to retrieve shadow information from CSAS data to improve target analysis and carry 3D reconstruction. Sub-aperture filtering is used to get a collection of images at various points of view along the circular trajectory and fixed focus shadow enhancement (FFSE) is applied to obtain sharp shadows. An interactive interface is also proposed to allow human operators to visualize these shadows along the circular trajectory. A space-carving reconstruction method is applied to infer the 3D shape of the object from the segmented shadows. The results demonstrate the potential of shadows in circular SAS for improving target analysis and 3D reconstruction.