基于Laplace的LSSIM图像配准算法

提出一种基于Laplace变换的图像配准算法. 首先利用经典的角点检测算法提取待匹配图像的特征点或角点; 其次利用相位相关法估算出两幅图像的重叠区域, 以缩小匹配范围; 然后对角点邻域模板区域施行Laplace变换; 最后利用基于改进的SSIM (结构相似性)作为相似性度量准则建立特征点之间的匹配关系. 实验结果表明, 该方法可以很好的完成特征点匹配, 匹配点对充足且具有很高的准确率, 而且对亮度差异具有一定的鲁棒性, 从而保证图像配准精度.

LSSIM Algorithm for Image Registration Based on Laplace

This paper presents a LSSIM algorithm for image registration. First extract the feature points from images by classic corner detection method; Then use phase correlation method to estimate the overlapping area between the two images; Then transform the neighborhood area of feature point with Laplace; Last, establish the matching relationship between the two images by the improved SSIM (structural similarity) method. Results show that the LSSIM method can complete a good job of feature point registration. The matching point pairs are not only adequate but also accurate and at the same time have certain robustness to brightness difference, so it can ensure the accuracy of image registration.