光学学报, 2019, 39 (10): 1001003, 网络出版: 2019-10-09   

基于水面特征波纹的水下运动目标Radon变换探测方法 下载: 1291次

Radon Transform Detection Method for Underwater Moving Target Based on Water Surface Characteristic Wave
作者单位
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, 北京 100081
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。
Abstract
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.

徐曼, 裘溯, 金伟其, 杨洁, 郭宏. 基于水面特征波纹的水下运动目标Radon变换探测方法[J]. 光学学报, 2019, 39(10): 1001003. Man Xu, Su Qiu, Weiqi Jin, Jie Yang, Hong Guo. Radon Transform Detection Method for Underwater Moving Target Based on Water Surface Characteristic Wave[J]. Acta Optica Sinica, 2019, 39(10): 1001003.

本文已被 5 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!