基于侧扫声呐的水下小目标检测技术研究

Research on small underwater target detection technology based on side-scan sonar

摘要:

针对水下小目标探测与识别难的问题，开展基于侧扫声呐的声呐图像滤波、图像分割及目标提取方法研究。常规滤波方法难以有效清除图像中存在的噪声，从而造成图像质量下降，本文采用非局部均值滤波算法与GPU加速的方法，在获得声呐图像较好处理效果的同时，满足水下小目标检测实时性的要求；同时采用膨胀算法与Canny边缘检测算法相结合的方式，实现了水下真假目标的有效区分。

Abstract:

In order to solve the problem of small underwater target detection and recognition, the methods of sonar image filtering, image segmentation and target extraction based on side-scan sonar are studied. Conventional filtering methods are difficult to effectively remove the noise in the image, resulting in degradation of image quality, in this pape, the non-local means filter algorithm and GPU acceleration method are used to obtain better processing results of sonar images, and to meet the real-time requirement of small underwater target detection, and adopts the method of combining the expansion algorithm with the Canny edge detection algorithm, effective discrimination of true and false underwater targets is realized.