基于分块形状特征的异源图像匹配方法

在基于特征的异源图像匹配中,由于成像原因导致的轮廓不完整会使得匹配难度增加。针对这一问题,提出了一种基于分块形状特征的匹配方法。首先从基准图和实时图中提取轮廓特征并对其进行分块,然后提取分块特征并归一化,最后采用加权相似性度量实现匹配定位。由于利用候选目标区域信息排除了虚警,进一步提高了匹配的正确性和鲁棒性。采用该方法对红外与可见光图像进行了测试。结果表明,本文方法具有较好的匹配性能。

Multi-sensor Image Matching Method Based on Block Shape Features

In the matching process of multi-sensor images based on features, the incomplete contour caused by imaging may increase the difficulty in image matching. To solve this problem, a novel image matching method based on block shape features is proposed. Firstly, the contour features are extracted from a reference image and a real-time image respectively and are divided into blocks hierarchically. Then, the block features are extracted and normalized. Finally, the weighted similarity measure is used to implement matching localization. Because the area information of a candidate target is used to exclude false alarms, the correctness and robust of the matching are further improved. The method is tested in the matching of infrared and visible images. The result shows that the proposed method has better matching performance for multi-sensor images.