基于贝叶斯决策的航空影像自动配准

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. 

Aerial Image Registration Based on Bayesian Decision Theory

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.