UFCLS线性光谱混合分析法在遥感图像分类识别中的效果分析
Effect Analysis of UFCLS Linear Spectral Mixture Analysis Method on Classification of Remote Sensing Images
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摘要: 用非监督全约束最小二乘法对线性光谱混合模型进行了反演,通过获得各像元组分的面积比图像来达到对各像元分类的目的。将非监督全约束最小二乘法的分类结果与有限光谱混合分析法的分类结果进行对比,结果表明,无论从分类效果还是计算时间上看,前者都优于后者。Abstract: The abundance fractions of endmembers in an image pixel are estimated by unsupervised fully constrained least squares (UFCLS) based on the inversion of linear spectral mixture method. The results of the experiment show that the effects are good. Compared to CSMA method, UFCLS method is better in both the effects of classification and the consumption of computation time.
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