SAR图像不确定轮廓相似度及其可信度构建方法

SAR图像相似度准则是目标识别、图像匹配等研究内容的基础，定义合理可靠的相似度将极大地提高SAR图像解译能力。该文针对SAR图像轮廓特点，提出一种基于不确定轮廓的相似度置信区间及其可信度构建方法。首先将SAR图像不确定轮廓模糊化得到相似度定义，进而通过分析模糊模型分布函数，在给定显著性水平下得到相似度置信区间，并给出可信度定义。实验结果表明，该方法对轮廓定位有一定容错性，对一定程度的断裂轮廓及多边缘轮廓也能得到合理的相似度范围和可信度，符合人眼视觉感知。

Construction of Similarity Measure and Its Credibility of Uncertain Contours in SAR Images

The similarity measures between SAR images are the basis for target recognition,classification,image registration and so on.The interpretation of SAR images can be improved obviously by defining reasonable and reliably similarity measure.In this paper,a confidence interval of similarity and the method of constructing credibility are proposed based on the characteristics of image contours.Firstly,the similarity measure is obtained by fuzzifying the uncertain contours in SAR images.Then,the confidence interval of the measure as well as the definition of credibility at a given confidence level are got by analyzing the distribution function of fuzzy model.The experimental results demonstrate that the proposed similarity measure between a given pair of images is robust to the location of image contours.Besides,it can also provide reasonable similarity with credibility of the fractured and multi-edged contours,which has not been presented by other methods.Moreover,it is consistent with human visual perception.