基于蚁群优化算法的SAR图像舰船检测研究  

Study on SAR image ship detection based on ant colony optimization algorithm

作　　者：李琳琳[1] 王纪奎[2] 宋艳芳[1] 

机构地区：[1]山东协和学院机电工程学院,山东济南250107 [2]积成电子股份有限公司电网自动化事业部,山东济南250100

出　　处：《齐鲁工业大学学报》2014年第2期80-83,96,共5页Journal of Qilu University of Technology

基　　金：山东省高等学校科技计划项目(J11LG79)

摘　　要：边缘检测作为提取图像边缘的重要方法在舰船检测中占有重要位置。采用蚁群优化算法通过调整动态阈值进行边缘检测。与传统边缘检测算子和小波变换算法对比采用蚁群优化算法进行舰船检测大大的减少了计算时间和代价,同时有效地提取了SAR图像的舰船目标和结构信息,保证了检测结果的准确性。蚁群优化算法在处理图像边缘检测等离散优化问题上具有很大的优越性,在图像处理中具有广阔的应用前景。Edge detection as an important image edge extraction method plays an important part in ship detection. Ant Colony Optimization algorithm was adopted in edge detection by adjusting threshold dynamically. Compared with the traditional edge detection operators and wavelet transform,ant colony optimization algorithm greatly reduces the ship detection computing time and cost,and extracts the targets and ship structure information in SAR image,ensures result accuracy effectively. Ant Colony Optimization algorithm has a lot of advantages in dealing with image edge detection and so on discrete optimization problems,it performs very broad prospect in image processing.

关 键 词：边缘检测 小波变换 舰船检测 蚁群优化算法 

分 类 号：TN953.7[电子电信—信号与信息处理]