基于梯度显著性的水面无人艇的海天线检测方法  

Sea Sky Line Detection Method of Unmanned Surface Vehicle Based on Gradient Saliency

作　　者：王博 苏玉民 万磊 庄佳园 张磊 

机构地区：[1]哈尔滨工程大学水下机器人技术国防科技重点实验室,黑龙江哈尔滨150001

出　　处：《光学学报》2016年第5期58-67,共10页Acta Optica Sinica

基　　金：国家863计划(2014AA09A509);国家自然科学基金(51009040);中央高校基本科研业务费自由探索计划(HEUCF150118)

摘　　要：水面无人艇技术在气象监测、海面搜救、对敌侦察、精确打击等方向发挥着越来越重要的作用,但实际海面环境中的云层辐射、波浪反射、气象条件等光学图像形成中的各种干扰因素,使海天线的准确检测难以实现。为了解决这一问题,提出一种基于梯度显著性的海天线检测方法,梯度显著性的计算有效增强了海天线的直线特征并抑制了各种干扰因素,采用区域生长方法实现了对海天线的检测和辨识,最后使用XL水面无人艇在实际海面环境下采集的光学图像进行验证,结果证明了所用方法的准确性和实时性。Unmanned surface vehicle（USV）plays a more and more important role in various areas such as meteorological monitoring,maritime search and rescue,enemy reconnaissance,and precision strike.However,special features in real marine environment such as cloud clutter,sea glint,and weather conditions result in various kinds of interference in optical images,which makes it very difficult to detect the sea sky line accurately.To solve this problem,a sea sky line detection method is proposed based on gradient saliency.The line features of sea sky line are enhanced effectively through the computation of gradient saliency;other interference factors are suppressed;sea sky line detection and identification are achieved by region growing method.In the end,the proposed method is tested on optical images fromXL＂USV in real marine environment and the experimental results demonstrate that the proposed method is significantly superior to other state-of-the-art methods in terms of detection rate and real-time performance.

关 键 词：成像系统 图像处理 海天线检测 梯度显著性 区域生长 直线特征 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]