多源遥感数据的融合和综合应用必须实行严格的配准，若将通过选取控制点的传统方法，用于成象特性差异较大的图象间配准就存在较大的误差，为解决该问题，研究发展了一种基于分窗口相关的图象配准方法，即采用移动窗灰度相关的方法对图象上的每一点进行搜索，来寻找最大相关位置，以达到精确配准的目的。通过将该方法应用于不同时相的TM图象、SAR图象、不同成象方式和不同分辨率的AVIRIS图象和航片间配准的实验表明，该方法能够有效地实现复杂图象间的精确配准，配准误差已达到子象素级水平。

In remote sensing applications, accurate registration is importment for data fusion and detection of object changes. When registering images with substantially different characteristics, the traditional method of tie points give inaccurate results. In this study, a registration method using a multi window cross correlation technique is developed. A moving window with different scales in the target image is cross correlation with a chosen fixed window in the reference image, and the best match is obtained to provide a satisfactory registration by comparing loop algorithm. Using cross correlation technique for separated windows from reference image, all the match location and the ratio between two images can be determined. Three registration tests employed this method were done between TM images at different time, SAR at different time, AVIRIS and aerial photo. Experimental results on sparately acquired TM images, SAR, AVIRIS images and aerial photos show that the described method can produce subpixel accuracy for registraction between complex images, and it is more convenience than the tie points methods.