SPIN-2 Panchromatic and SPOT-4 Multi-Spectral Image Fusion Based on Support Vector Machine
基于支持向量机的SPIN－2影像与SPOT－4多光谱影像融合研究

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.