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.