一种新的卫星多光谱图像自动配准算法

A New Automatic Band Registration Algorithm for Satellite Multispectral Remote Sensing Images

针对小卫星独立相机多光谱成像系统波段间配准的非线性误差问题,提出了一种多光谱图像波段间自动配准算法,该算法综合利用互信息、遗传算法和MQ几何校正模型进行多光谱图像的自动配准。在算法中,以互信息作为配准的相似性度量,获得了很高的配准精度;利用遗传算法的快速搜索特性,可以较快的完成搜索并获得整体的最优解;利用MQ几何模型可以精确的建立图像之间的几何关系。试验表明该算法对于多光谱图像波段间非线性几何关系,能够取得非常高的波段间自动配准精度,整体配准误差在一个像元以内。

Satellite multi-spectral images which captured from independent camera photography system of small satellite have nonlinear errors in spatial position. To this complicated problem, the paper introduces an automatic registration method to match muhi-spectral images automatically, in which the mutual information, genetic algorithm and MQ geometric correction models are intergraded. In its algorithm, the mutual information is used as a similarity function of the registration problem, which can achieve an accurately registration precision： and the genetic algorithms are utilized to search the optimization value fast by its characteristics of finding global optima rapidly and efficiently; Meanwhile, the MQ geometric correction models are also adopted to develop a correspondence between the input and output images quickly. From the experimental results, it seems that this method can achieve a better accurate automatic registration results in bands nonlinear geometric relationships between multi-spectral images, whose error of the entire matching is less than a pixel.