There exist some shortages in the traditional image matching algorithm based on gray degree, such as huge quantities of calculation, relatively low accuracy, and too many restrictions in application. In order to solve these problems, this paper puts forward an optimized remote sensing image matching algorithm. The main ideas include the following several aspects: On the basis of confirming the subimage of the target image by understanding prior knowledge of remote sensing image, the first step is to search the subimage of the target image non-equidistantly with dynamic template, the second step is to locate the target position by two threshold gray degree correlation coefficients and conformal transform, and the last step is to judge the target position of the ground control point not recognized correctly by the spatial location relations of ground control points. The work flow is introduced in detail. Moreover, a comparison experiment on traditional and modified image matching algorithms is performed with an ASTER image and a TM image. From the results obtained, we can reach the conclusion that the modified algorithm is superior to the traditional algorithm in that it has much more higher accuracy and efficiency than the latter and hence it should have higher adaptability and applicability.