A Comparison of Texture Feature Algorithms for Urban Settlement Classification

机译：城市定居分类纹理特征算法的比较

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Texture features derived using Haralick's Gray-Level Cooccurrence Matrix (GLCM) are by far the most popular in urban remote sensing research ?? but are they the best features for every application? In order to select the most appropriate texture algorithm for an automated informal settlement classification system, we performed an experiment to compare the performance of the GLCM with that of other texture features. The performance of a texture feature is measured by computing the classification accuracy achieved on a supervised set of images spread over 8 settlement classes, focusing on informal and low-cost housing. The results show that GLCMs perform very well, but that Local Binary Pattern texture features have a small advantage in this classification problem.

机译：使用Haralick的灰级Cooccurrence矩阵（GLCM）导出的纹理特征是迄今为止在城市遥感研究中最受欢迎？但它们是每个应用程序的最佳功能吗？为了为自动非正式结算分类系统选择最合适的纹理算法，我们执行了一个实验，以比较GLCM与其他纹理功能的性能。通过计算在8份沉降类别的监控图像上实现的分类精度来测量纹理特征的性能，专注于非正式和低成本的住房。结果表明，GLCMS表现得很好，但本地二进制图案纹理特征在该分类问题中具有很小的优势。

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《International Geoscience Remote Sensing Symposium》|2008年||共15页
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Ella L. P. Abeigne; van den Bergh F.; van Wyk B. J.; van Wyk M. A.;
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中图分类 P3-53;
关键词
Settlement classification; Texture features;

机译：结算分类;纹理特征;

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4. A Comparison of Texture Feature Algorithms for Urban Settlement Classification [C] . Ella L. P. Abeigne, van den Bergh F., van Wyk B. J., International Geoscience Remote Sensing Symposium . 2008

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A Comparison of Texture Feature Algorithms for Urban Settlement Classification

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