基于水面特征波纹的水下运动目标Radon变换探测方法  

Radon Transform Detection Method for Underwater Moving Target Based on Water Surface Characteristic Wave

作　　者：徐曼 裘溯 金伟其 杨洁 郭宏 Xu Man;Qiu Su;Jin Weiqi;Yang Jie;Guo Hong(Key Laboratory of Photoelectronic Imaging Technology and System(Beijing Institute of Technology),Ministry of Education,School of Optics and Photonics,Beijing Institute of Technology,Beijing 100081,China)

机构地区：[1]北京理工大学光电学院光电成像技术与系统教育部重点实验室

出　　处：《光学学报》2019年第10期25-37,共13页Acta Optica Sinica

基　　金：国家自然科学基金(6157031371)

摘　　要：针对在光电偏振成像模式下缺乏行之有效的水下运动目标探测方法的问题,提出了一种基于水面特征波纹的水下运动目标检测算法。通过海面风生重力波模型和水下运动目标的水面特征波纹模型,仿真得到不同状态下的海面混合波纹图像,用于算法研究及证明;采用Radon变换提取波纹的线性特征,并通过均值滤波和标准归一化处理消除Radon变换对检测的影响;采用双邻域自适应门限法提取Radon变换域中的局部峰值点,利用连续小波变换进行特征提取,并用支持向量机(SVM)判断峰值点真伪,提高检测的准确率。实验结果证明了本文算法对特征波纹检测的可行性。该算法为探测水下运动目标提供了一种新的有效途径。An underwater moving target detection algorithm based on water surface characteristic wave is proposed to overcome the shortage of effective detection methods for photoelectric polarization imaging modes. Based on the wind-induced gravity wave model and the water surface characteristic wave model of an underwater moving target, the mixed wave images under different states are simulated and used for the research of the algorithm. The algorithm uses the Radon transform to extract the linear wave characteristic, and average filter and standardization are employed to preprocess images, thereby eliminating the adverse effect of Radon transform on detection. The double-neighborhood adaptive threshold method is employed to extract partial peak points in Radon transform domain. The algorithm employs continuous wavelet transform to extract features and support vector machine to judge the peak points, thereby improving the detection accuracy. The experimental result shows that the algorithm is feasible for characteristic wave detection, which also provides a new way for underwater moving target detection.

关 键 词：海洋光学 RADON变换 特征波纹 尾迹检测 水下运动目标 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] TP751[自动化与计算机技术—计算机科学与技术]