Texture Classification of Aerial Images Based on Support Vector Machines

This paper applies the support vector machines(SVM) to the texture classification of aerial images.The SVM is a new learning machine for two-group classification problems.SVM approach uses the kernel method to map the data with a non-linear transformation to a higher dimensional space and in that space attempts to find a linear separating surface between the two classes.The complexity relies on the number of samples,especially the number of support vector.This can solve the problem of small number of samples and higher dimensional features.The experiments show that the results are better.