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基于贝叶斯决策的航空影像自动配准

张帅毅,  李永树,  蔡国林

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文章导航 > 西南交通大学学报  > 2015 >  28(1): 161-166.
张帅毅, 李永树, 蔡国林. 基于贝叶斯决策的航空影像自动配准[J]. 西南交通大学学报, 2015, 28(1): 161-166. doi: 10.3969/j.issn.0258-2724.2015.01.024
引用本文: 张帅毅, 李永树, 蔡国林. 基于贝叶斯决策的航空影像自动配准[J]. 西南交通大学学报, 2015, 28(1): 161-166. doi: 10.3969/j.issn.0258-2724.2015.01.024
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ZHANG Shuaiyi, LI Yongshu, CAI Guolin. Aerial Image Registration Based on Bayesian Decision Theory[J]. Journal of Southwest Jiaotong University, 2015, 28(1): 161-166. doi: 10.3969/j.issn.0258-2724.2015.01.024
Citation: ZHANG Shuaiyi, LI Yongshu, CAI Guolin. Aerial Image Registration Based on Bayesian Decision Theory[J]. Journal of Southwest Jiaotong University, 2015, 28(1): 161-166. doi: 10.3969/j.issn.0258-2724.2015.01.024
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基于贝叶斯决策的航空影像自动配准

doi: 10.3969/j.issn.0258-2724.2015.01.024
基金项目: 

中央高校基本科研业务费专项资金资助项目(2682013ZT26)

详细信息
    作者简介:

    张帅毅(1988-), 男, 博士研究生, 研究方向为摄影测量与图像模式识别, E-mail:shuaiyigis@gmail.com

    通讯作者:

    李永树(1957-), 男, 教授, 博士生导师, 主要研究方向为GIS理论及应用、遥感制图、变形监测等, E-mail:yshli@swjtu.edu.cn

Aerial Image Registration Based on Bayesian Decision Theory

    摘要
  • 摘要: 为消除像点投影差对航空影像目标监测中影像配准的影响,提出了一种基于贝叶斯决策理论的像点投影差消除方法.该方法通过推导分析像点投影差的分布规律及其对影像配准的影响,设置训练样本区,提取大量特征匹配对,计算得到投影差分布参数,并基于贝叶斯决策理论构建了像点投影差消除准则.为验证其有效性,选用KIT AIS影像数据进行了实验,比较分析了投影差消除前后的配准影像结果.分析结果显示,消除后差分视觉效果得到改善,信息熵减小10%,表明本文方法可有效提高航空影像配准的精度.

     

    Abstract: To eliminate the influence of projection difference on aerial image registration in object monitoring, a new image registration method was proposed based on Bayesian decision theory. Distribution rule of projection difference was derived and its impact on image registration was analyzed. A large number of feature matches were extracted to calculate the distribution parameters within the pre-set training sample area. The distribution rule was tested with KIT AIS dataset, and the registered images before and after eliminating projection difference were compared. The difference image results show an improved visual effect and 10% entropy decrease after elimination, which proves that the proposed algorithm is effective to improving the accuracy of aerial image registration.

     

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出版历程
  • 收稿日期:  2013-09-12
  • 刊出日期:  2015-02-25

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