对基于特征匹配的影像可匹配性评价方法进行了探讨.从分析影像所包含的信息量入手,提出了通过计算影像的信息熵和累加梯度值进行基于特征匹配的影像可匹配性评价方法.通过基于角点特征和Hausdorff距离的影像匹配实验,发现影像信息熵和累加梯度值与影像可匹配性(即正确匹配概率)之间存在很强的相关性,尽管由于地表景观的不同,表现出的具体规律略有差异,但都表现出匹配正确率随影像信息熵和累加梯度的增大而增大的趋势.因此,可通过对影像信息量的评价来进行基准图的自动选取和飞行路径的规划;在实时匹配导航过程中,可根据获取的每一实时影像所含信息量,来决定是否进行匹配,这样既可以保证匹配的正确性,避免误导,又可节省匹配时间.提出方法对基于灰度相关的影像可匹配性评价具有借鉴意义.

The evaluating approach of image＇s ability to obtain correct matching based on image feature matching is discussed.It is suggested that information entropy and summation of image gradient can be used for evaluating image＇s ability to obtain correct matching.By the test of image matching based on comer feature and Hausdorff distance, the relation among correct matching probability and information entropy and summation of image gradient is discovered.Strong correlation exists among correct matching probability and information entropy and summation of image gradient.It is shown that correct matching probability is increasing with the increasing of information entropy and summation of image gradient, although concrete rule is of tiny difference because of the field surface landscape＇s difference. Therefore, through calculating image＇s information content, automatic reference image selection and planning navigation route can be done.During real-time matching navigation, whether matching carded out or not would be confirmed by evaluation real-time image＇s information content.To do as such,higher correct matching probability would be obtained, misguide would be avoided and matching time would be saved. The method of the paper can also be available in image evaluation based on gray-level image matching.