Hyperspectral image classification based on fuzzy support vector machine

Support Vector Machine(SVM) has a good identification effect in HSI classification.However,the unclassifiable regions often exist in SVMbased classification with multi-classes included.Under this condition,this paper proposes an FSVM technique based on 1-a-1 SVM,and applies it to HSI classification.The results show that it not only reduces the existence of unclassifiable regions,but also gets better classification accuracy than the traditional SVM.