An underwater binocular stereo matching algorithm based on the best search domain
This work aims to improve the accuracy of underwater distance measurement for applications requiring spatial point coordinates, such as underwater robotics or mapping, by overcoming limitations of traditional stereo vision in aquatic environments. It is an incremental improvement for a specific domain.
This paper addresses the challenge of underwater binocular stereo matching where traditional epipolar constraints and calibration methods fail due to illumination and imaging model changes. It proposes a new real-time underwater calibration method and a matching method based on the best search domain to improve the accuracy of underwater distance measurement.
Binocular stereo vision is an important branch of machine vision, which imitates the human eye and matches the left and right images captured by the camera based on epipolar constraints. The matched disparity map can be calculated according to the camera imaging model to obtain a depth map, and then the depth map is converted to a point cloud image to obtain spatial point coordinates, thereby achieving the purpose of ranging. However, due to the influence of illumination under water, the captured images no longer meet the epipolar constraints, and the changes in imaging models make traditional calibration methods no longer applicable. Therefore, this paper proposes a new underwater real-time calibration method and a matching method based on the best search domain to improve the accuracy of underwater distance measurement using binoculars.