A high-precision registration algorithm for heterologous image based on effective sub-graph extraction and feature points bidirectional matching

Xiujie Qu, Yue Sun, Yue Gu, Shuang Yu, Liwen Gao
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引用次数: 2

Abstract

Aiming at solving the problem of low matching accuracy caused by different imaging mechanism of heterologous image, we propose a novel image registration algorithm based on effective sub-image extraction and bidirectional matching for surf feature points. The algorithm adopts a coarse-to-fine matching strategy. Firstly, we transform the edge image into frequency domain through fast Fourier transform, and roughly estimate transform parameters using the cross power spectrum; secondly, we divide the images after rough matching into several sub-graphs, from which we will pick out the effective sub-graph in terms of normalized mutual information, then we match bidirectionally the feature points of effective sub-graph pair according to time domain features, thus obtaining accurate transformation parameters, completing the fine matching. Experimental results of heterologous images in different scenarios show that, the proposed algorithm effectively improves the registration accuracy which is up to sub pixel level.
一种基于有效子图提取和特征点双向匹配的异源图像高精度配准算法
针对异源图像成像机制不同导致匹配精度低的问题,提出了一种基于有效子图像提取和冲浪特征点双向匹配的图像配准算法。该算法采用一种从粗到精的匹配策略。首先,通过快速傅里叶变换将边缘图像变换到频域,并利用交叉功率谱粗略估计变换参数;其次,将粗糙匹配后的图像分成若干子图,根据归一化互信息从中挑选出有效子图,然后根据时域特征对有效子图对的特征点进行双向匹配,从而获得准确的变换参数,完成精细匹配;不同场景下的异源图像实验结果表明,该算法有效地提高了配准精度,配准精度达到亚像素级。
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