一种利用多光谱双向检测和多尺度角特征验证的角提取方法

A Corner Extraction Method Based on Multi-spectral Double-directional Detection and Multi-scale Corner-characters Validation

联合TK(Tomasi-Kanade,TK)角检测器和COVPEX(corner validation based on corner property ex-traction,COVPEX)角验证算法进行IKONOS多光谱影像的角提取。角提取对比实验结果说明,本方法适合用于多光谱高分辨率影像,其角提取结果的精确性和合理性均有较大程度的提高。

In this paper, TK （Tomasi-Kanade） corner-detector and COVPEX （Corner validation based on corner property extraction, COVPEX） algorithm are combined to extract corners from IKONOS Multi-spectral images. Firstly, we use TK corner-detector and find that the detector is sensitive to the corner-orientation and corner-contrast changes. It always results in ＂under-detection＂. Aim at these defects of TK corner-detector, we improve it and propose the Multi-spectral double-directional TK corner detector. To reduce sensitive degree to the corner-contrast, the new detector uses multi-spectral data to estimate corner-signifi- cance of a pixel. Moreover, the corner-clusters are presented in the processing results, which destroy uniqueness of corner. In order to reduce the proportion of pseudo-corners, we propose multi-scale COVPEX algorithm which uses multi-scale corner-characters to validate corners. In the meantime, based on the local minimum value theory, the corner-cluster removing method is also proposed to preserve uniqueness of corner. Finally, the comparative experiment results of corner extraction show that the proposed method is suitable for multi- spectral high-resolution imagery, accuracy and rationality of the extracted corners are considerably improved.