一种基于小波的多传感器图像配准算法

Huang Xi-shan, Chen Zhe
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引用次数: 23

摘要

多传感器图像具有不同的灰度特征,但在大多数情况下保留了代表区域边界的轮廓。提出了一种基于轮廓的配准算法,该算法使用区域边界和其他定义良好的边缘作为匹配基元。该算法将不变矩与轮廓的方向函数相结合,建立CCD和红外等两幅图像中轮廓的对应关系。提出了一种改进的小波模糊轮廓提取方法。在特征匹配方面,提出了一种方向函数匹配方法,并将其集成到不变矩中与提取的轮廓相对应。具有至少两个突出点的轮廓和仅具有一个突出点的轮廓分别匹配。将对应的突出点作为控制点对,并在此基础上估计变换参数。该方法能够自动实现,对于轮廓信息保存良好的图像对具有较好的效果。利用CCD和红外图像的实验结果验证了本文提出的理论和算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A wavelet-based multisensor image registration algorithm
Multisensor images have different gray level characteristics while contours representing region boundaries are preserved in most cases. A contour-based registration algorithm which uses region boundaries and other well-defined edges as matching primitives is presented. This algorithm integrates the invariant moments with the orientation function of the contours to establish the correspondences of the contours in the two images, e.g. CCD and infrared (IR). The improved wavelet-based fuzzy contour extraction is developed. For the feature matching, an orientation function matching is proposed and integrated to the invariant moments to correspond the extracted contours. The contours with at least two salient points and others with only one salient point are matched separately. The correspondence salient points are used as control-point pairs, and the transformation parameters are estimated based on them. This approach implements automatically and works well for the image pairs in which contour information is well preserved. Experimental results for the CCD and IR images are used to test and verify the theory and algorithm presented in this in this paper.
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