关键词: 卫星数字图像, 分形, 神经网络, 纹理结构特征

Abstract: It is a new approach to improve the accuracy of image classification in combining spectral feature with texture and structural features of ground objective on satellite image. Based on the recognizable characteristics of satellite image, it is introduced how to describe and capture texture and structural features of ground objective by the Discrete Fractional Brownian Motion model. Furthermore, neural networks are used for classification tool of satellite image. In classification spectral feature, texture and structural features of ground objective are used for the category of an IRS-1C satellite image. The category result shows this approach is better than the maximum likelihood classifier.

Key words: satellite image classification, fractal, neural networks, texture and structural characteristics