基于双搜索蜂群算法的四元数彩色遥感图像边缘检测  

Double Search Colony Algorithm for Color Remote Sensing Image Edge Detection Based on Quaternion Representation

作　　者：蒲国林[1] 邱玉辉[2] 

机构地区：[1]四川文理学院计算机学院,达州635000 [2]西南大学计算机与信息科学学院,重庆400715

出　　处：《计算机科学》2016年第7期310-313,共4页Computer Science

基　　金：国家自然科学基金:基于情感语义的全局均衡智能推荐理论与应用研究(61152003);国家档案局科技计划项目:基于大数据的档案数据去重模型与方法研究(2014-X-65);四川省教育厅科研项目:人工蜂群算法在网络突发事件预测中的应用研究(15ZB0323);四川文理学院智能计算与物联网工程技术中心资助

摘　　要：随着遥感图像大数据的出现,常见的彩色遥感图像边缘检测方法运算量大、速度慢、效果差等缺点越来越明显。以四元数表示彩色像素为基础,改进人工蜂群算法的单一搜索方程,加大雇主蜂搜索范围,加入跟随蜂莱维飞行因子,提出了基于双搜索方程的人工蜂群算法。实验结果表明,该算法具有计算量小、去噪能力强、边缘检测效果好等优点。该算法能有效地应用于从遥感图像中获取识别目标。With the advent of big data of remote sensing image, common color remote sensing image edge detection has a greater amount of computation, lower speed, worse effect and more obvious shortcomings. We used a quaternion vector to represent a color pixel, improved artificial bee colony algorithm for single search equation, expanded employed bee search area, and added Levy flight factor in the equation of onlookers, proposed an artificial bee colony algorithm based on dual-search equation. Experimental results show that improved double search artificial bee colony algorithm for remote sensing image edge detection not only significantly reduce the amount of computation of edge detection, but also reduce the noises in the color remote sensing image. The proposed algorithm can be effectively applied to obtain the recognition target from remote sensing image.

关 键 词：蜂群算法 彩色遥感图像 双搜索方程 边缘检测 四元数 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]