An appraisal of backscatter removal and refraction calibration models for improving the performance of vision-based mapping and navigation in shallow underwater environments

Abstract

Vision-based mapping (VbM) is one of the fundamental origins of automation in remote and autonomous spatial data acquisitions. Complexity in obtaining accurate data arises when such a method is applied in the underwater environment. Non-uniform illumination and refraction distortion are the most common problems encountered in underwater VbM. This study addresses this by employing backscatter removal to enhance image clarity and a pinhole-axial (Pinax) camera model to adjust the refraction distortion. In particular, the methods are computed in the robot operating system (ROS), publishing the enhanced images as separated image nodes in real-time and enabling seamless integration to the VbM pipeline. It is argued that the proposed VbM-dedicated models can significantly improve the feature detection method and conformity of object positions underwater around the camera's motion. Simulation datasets are generated to evaluate the sensitivity to varying turbidity levels to test the method's sensitivity. Additionally, field experiments with GoPro 10 hardware in Pramuka Island Waters, Indonesia, offer real-world context for the study's relevance to distinct underwater circumstances. Furthermore, additional visual-inertial datasets quantify the overall performance, especially in retrieving metric positioning information. The research shows efficient backscatter removal improves feature detection robustness, especially in murky water conditions. Refraction correction eliminates the bowing effect from missing ground control points in underwater environments. The study is significant because it emphasizes how vital image enhancement and refraction calibration are to obtaining <4 % trajectory error of VbM. Overall, the proposed VbM pipeline can maintain <5 cm trajectory error compared to the standard VbM pipeline. The results highlight the need for a comprehensive strategy to advance underwater mapping and navigation technology to deliver accurate and dependable outcomes in various underwater situations.