Single spatial feature is used in the traditional spectral and spatial feature fusion,which does not make full use of the advantage of high spectral and spatial resolution.In order to overcome the shortage,a method based on texture feature and extend morphological profile fusion for hyperspectral image classification was proposed.Firstly,with the principle component analysis,the hyperspectral image dimension was reduced and the spatial correlation was eliminated,then using the gray level co-occurrence matrix the texture features for each principle component were extracted and the extend texture features were got,lastly combined the extend morphological profile and part spectral features hyperspectral image is classified.The experiments show that the proposed method can overcome the limitation of traditional spectral feature classification and improve the accuracy of hyperspectral images classification.