MULTI-SOURCE REMOTE SENSING IMAGE FUSION BASED ON SUPPORT VECTOR MACHINE附视频

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-2and multi-spectral remote sensing data S POT-4.Firstly,the new method is established by building a model of remote sensing im age fusion based on SVM.Then by using SPIN-2data and SPOT-4data,image classifi-cation fusion is tested.Finally,an evaluation of the fusion result is ma de in two ways.1)From subjectivity assessment,the spatial resolution of the fused i mage 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 bett er.As a whole,the re-sult shows that the accuracy of image fusion based on SVMis high and the SVM algorithm can be recommended for app lica-tion in remote sensing image fusion p rocesses.