一种声纳图像的三维重建方法

A Three-dimensional Reconstruction Method of Sonar Image

声纳是重要水下探测与感知设备,但普通的二维声纳图像包含信息较少,不利于直观的理解。本文基于声纳图像的映射原理、利用多视角的几何映射关系建立一种特征点的三维重建方法。对声纳的映射与逆映射原理进行描述与分析,建立一种对高度特征分段分层搜索的重建方法,实现旋转、平移参数已知情况下的重建;对参数未知的情况,利用粒子群优化算法和少量特征点获得参数的估计,在此基础上实现更多特征点的重建;最后增加传感器对旋转平移参数带有误差的估计,实现重建精度大幅度地提升。该方法对特征点的数量以及重建环境的变化不敏感,是一种适应性好、鲁棒性较强的方法。

Sonar is an important equipment for submarine detection and perception,but usual two-dimensional sonar images contain fewinformation and can not be comprehended intuitively. Depending on mapping theory of sonar image and using sonar multiple viewgeometry a three-dimensional reconstruction method for feature points is proposed in this paper.The theories of sonar mapping and their inverse mapping are described for building a threedimensional reconstruction method searching height feature in different segmental arc of every layer,which could realize reconstruction under the condition that rotation and translation parameters are known. Corresponding to situations that those parameters are not known,particle swarm optimization algorithm is used to estimate parameters via using fewfeature points. Then more feature points are reconstructed subsequently by estimated parameters. At the end of this paper,the precision is improved drastically by appending rotation and translation parameters which are estimated by sensors with some errors. This described method is not easy to be obstructed by the number of feature points or reconstruction of scene,and hasgood adaptation as well as robustness.