An Automatic Sonar Target Shadow Extraction Approach for Rapid Seafloor 3-D Perception Using a Single Acoustic Camera

This article proposes an automatic sonar target shadow extraction approach based on a single acoustic camera to enable efficient 3-D perception of seafloor environments. The acoustic camera, a compact high-resolution forward-looking sonar (FLS), functions effectively in low-visibility conditions such as turbid and dark underwater environments. However, owing to the unique mechanism of sonar imaging, the captured 2-D sonar images generally lack elevation (height) information, thereby constraining rapid 3-D seafloor perception. This study estimates target height by leveraging the cast shadow clues present in sonar images, in combination with the sensitivity of sonar to subtle variations in these visual clues. Using shadow information to solve seafloor target height is a classic paradigm in sonar visual applications, but traditional methods do not work well in complex seabed environments. Therefore, this study proposes a comprehensive shadow extraction approach based on deep learning to overcome these limitations. First, a learning-based extraction framework is employed to automatically identify cast shadows of sonar targets, addressing challenges posed by low signal-to-noise ratios (SNRs) and poor contrast. To improve the accuracy of shadow labeling, a sonar simulator is utilized to assist the annotation process by providing reference data for cast shadow identification. Then, by combining the extracted shadow data with the altitude difference derived from sonar, the seafloor target height is quickly resolved. Unlike previous 3-D reconstruction pipelines, the proposed method does not rely on numerous overlapping views or complex elevation assumptions, enabling an efficient estimation of target height. Validation in an acoustic pool experiment shows that this method can reliably achieve efficient 3-D seafloor perception, potentially serving as a pivotal technology to support autonomous operations of marine robots in unknown seafloor.