The threshold of NDVI classification is one of the most popular methods in the classification of remote sensing image.However

based on spectrum characteristics of objects

it cannot correctly identify objects with the same spectrum characteristics and therefore cannot reach the required accuracy.In this paper

we take an area of the upper part of Xitiaoxi River in Anji County as an example and discuss the method of combining texture of high-resolution images with spectrum to improve the accuracy of extracted information of SPOT5 image.Firstly

principal components are extracted from SPOT5 image

and high-resolution texture information is acquired by means of the algorithms of signal decomposition and reconstruction of（Mallet’s） Wavelet.Subsequently textures of the SPOT5 image are analyzed using Gray Level Co-occurrence Matrices and selected statistic index.Then the threshold is selected and an optimal threshold is obtained according to contrast and entropy.Objects with same spectrums

such as residence and water body

are identified using image segmentation in virtue of the optimal threshold.Finally

the final result is compared with the classification results based on single spectrum or texture.The result shows that objects with same spectrum are well identified by using texture analysis in image classification

and higher accuracy is obtained than using single spectrum or texture analysis.