基于独立成分分析的遥感影像可匹配性度量(英文)

Remote Sensing Image Matching Performance Metric Based on Independent Component Analysis

为了提高景象匹配中基准图制备的效率和可靠性,对遥感影像图源的可匹配性进行分析,提出一种基于独立成分分析的遥感影像可匹配性度量方法.利用独立成分分析提取纹理基函数,并计算其概率分布,确定可匹配区域;然后定义可匹配区域所占面积比例指标、离散性指标和稳定性指标;最后,利用三个指标构建遥感影像可匹配性度量模型.实验表明,该遥感影像可匹配性指标与实际匹配概率相关性强,提高了基准图制备的可靠性,能够满足景象匹配图源筛选的实际需求.

To improve the reliability of reference map preparation for scene matching, it is necessary to analyze the matching performance of remote sensing image. Remote sensing image matching performance metric was proposed based on independent component analysis. Firstly, texture basis functions are produced based on independent component analysis and a set of probability functions that describe the coefficients distribution corresponding to each of the texture basis functions are calculated to extract matching regions. Secondly, the area ratio index, distribution index and stability index for matching regions are defined. Lastly, remote sensing image matching performance metric is constructed based on the three indexes. The experiment shows that the proposed remote sensing image matching performance metric index is highly correlated to real matching probability. It improves the reliability of reference map preparation and can meet the need of remote sensing images selection for scene matching.