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Multi-Classifier Systems (MCSs) of Remote Sensing Imagery Classification Based on Texture Analysis

机译:基于纹理分析的遥感图像分类多分类器系统(MCSS)

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This article concerns methods of improving the accuracy of land cover maps using Very High-resolution Satellites (VHRS). It discusses two methods for increasing the accuracy of classifiers used in land cover mapping. One is texture analysis using GLCM method and the other is multiple classifier system (MCSs) using voting rules. A case study of QuickBird Imagery of an area in Chenggong County of Yunnan Province is conducted based on an analysis of QuickBird imagery. The experiment results show that these two methods can improve the accuracy greatly. The applying of texture bands makes an increase of 2.6816%, and the MCSs make an increase of 3.9512%.
机译:本文涉及使用非常高分辨率卫星(VHRS)提高陆地覆盖图的准确性的方法。它讨论了增加陆地覆盖映射中使用的分类器准确性的两种方法。使用GLCM方法是纹理分析,另一个是使用投票规则的多种分类器系统(MCS)。基于Quickbird图像的分析,进行了对云南成贡县Quickbird图像的案例研究。实验结果表明,这两种方法可以大大提高精度。纹理频带的应用增加2.6816%,MCS增加3.9512%。

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