遥感影像融合是解决多源海量数据富集表示的有效途径之一。针对高分辨率遥感数据SPIN-2(2m)与多光谱遥感数据SPOT-4(20m)的影像融合，提出了基于支持向量机(SVM)的遥感影像融合的新方法。建立了基于SVM的遥感影像融合模型，并进行了分类融合实验，实验效果较好。最后给出了分类融合评价。结果表明，支持向量机可用于遥感影像融合，且分类融合精度较高。

Remote Sensing image fusion is an effective way to use the large volume of data from multi-source images.This paper introduces a new method of remote sensing image fusion based on support vector machine (SVM), using high spatial resolution data SPIN-2 and multi-spectral remote sensing data SPOT-4.First the new method is established by building a model of remote sensing image fusion based on SVM.Then using SPIN-2 data and SPOT-4 data, to test image classification fusion.Finally, an evaluation of the fusion result is made in two ways: (1)From subjectivity assessment, the spatial resolution of the fused image is improved compared to the SPOT-4, and it is clearly that the texture of the fused image is distinctive; (2)From quantitative analysis, the effect of classification fusion is better.As a whole, the result shows that the accuracy of image fusion based on SVM is high and the SVM algorithm can be recommended for application in remote sensing image fusion processes.