A hyperspectral image with complex background can be regarded as the components of different textures,the statistical distribution characteristic of which can be described by Gaussian model.Based on the model,a new algorithm is designed to segment the complex background into homogenous regions,breaking through the limits of size and form of the anomaly regions.The background distribution characteristic of hyperspectral image is described by 3 D Markov model.The model parameters are obtained by the Max Likelyhood Estimation algorithm.Then the texture segmentation and the anomaly detection algorithm are achieved based on the model parameters and the pixel statistical characteristic respectively.
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高旭辉,祁蒙.基于三维纹理分割的高光谱图像异常检测[J].激光与红外,2012,42(5):561~566 GAO Xu-hui, QI Meng. Anomaly detection based on 3 D texture segmentation for hyperspectral image[J]. LASER & INFRARED,2012,42(5):561~566