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 highspatial resolution data SPIN-2 and multi-spectral remote sensing data SPOT-4. Firstly, the new method is established bybuilding a model of remote sensing image fusion based on SVM. Then by using SPIN-2 data and SPOT-4 data, image classification fusion is tested. 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 thefused 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.