基于萤火虫最优偏差算法的农田红外目标检测研究  

Infrared target detection based on firefly optimal deviation algorithm

作　　者：周琳[1] 李红娟[1] 

机构地区：[1]河南牧业经济学院,河南郑州450045

出　　处：《浙江农业学报》2016年第7期1243-1248,共6页Acta Agriculturae Zhejiangensis

基　　金：中国国家专利(CN202600467U);河南省教育厅"十五"教育科学规划课题(2005-JKGHAZ-086);河南省社科联课题(SKL-2011-1927)

摘　　要：为了提高农田红外目标检测的性能,采用萤火虫最优偏差算法对其进行研究。首先,建立红外目标检测模型,构造红外图像目标灰度值最优偏差估计;然后,萤火虫算法在决策域范围内更新;接着,萤火虫在寻优分析中以红外点目标成像的艾里斑能量分布作为萤火虫适应度函数,且给出算法实现流程;最后,实验仿真显示,本文算法能够检测出红外目标区域,边缘定位准确,同时检测效率较高。In order to improve the performance of infrared target detection , firefly optimal deviation （ FOD） algorithm was proposed.First, infrared target detection model was established , and structure of infrared image target gray value of optimal bias was estimated .Second, firefly update was adopted in region decided range .Third, infrared point tar-get imaging of Airy spot energy distribution was considered firefly fitness function in optimization , and the algorithm flow was given.Finally, simulation showed that FOD algorithm could detect the target region in infrared image with accurate edge location and higher detection efficiency .

关 键 词：萤火虫 最优偏差 红外目标 检测 灰度值 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]