相控阵三维摄像声纳的自适应阈值选取

Selection of adaptive threshold for phased array 3D sonar

针对相控阵三维摄像声纳阈值选取的问题,提出了一种新的自适应阈值方法。该方法首先根据检测到的各个波束所属的边缘模式,统计各个波束的邻域对称性,并利用该对称性对原始的基于波束强度的置信度图像进行修正。再采用最大熵原理,计算适用于新的置信度图像的自适应阈值。试验结果表明:该算法能够有效地区分物体区域和背景区域,而所需的计算量仅与常规的空域滤波方法处于同一量级。该自适应阈值算法适合于相控阵三维摄像声纳系统的实时应用。

An adaptive threshold method was proposed for phased array 3D sonar systems.First,the beams of were classified into several edge modes and the beam-strength based confidence image was modified by checking the neighborhood symmetry of each beam.Next,the principle of maximum entropy was introduced to search the optimal adaptive threshold for the new confidence image.Experimental results show that the proposed method can distinguish the objects and backgrounds effectively while requiring similar computation as conventional spatial filter methods.This threshold method is suitable for real-time applications in phased array 3D sonar systems.