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首页> 外文期刊>Geoscience and Remote Sensing, IEEE Transactions on >Unsupervised Land Cover/Land Use Classification Using PolSAR Imagery Based on Scattering Similarity
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Unsupervised Land Cover/Land Use Classification Using PolSAR Imagery Based on Scattering Similarity

机译：基于散射相似度的基于PolSAR影像的无监督土地覆盖/土地利用分类

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摘要

This paper presents a new unsupervised land cover/land use classification scheme using polarimetric synthetic aperture radar (PolSAR) imagery based on polarimetric scattering similarity. Compared with the $H$/alpha classification scheme based on a dominant “average” scattering mechanism, the proposed scheme has such advantages as the following: 1) The major scattering mechanism represents a target scattering in the low-entropy case; 2) it also represents both the major and minor scattering mechanisms in the medium-entropy case; and 3) all the scattering mechanisms in the high-entropy case can be represented. The major and minor scattering mechanisms have been identified automatically based on the relative magnitude of multiple-scattering similarities. The canonical scattering corresponding to maximum scattering similarity is regarded as the major scattering mechanism. The result obtained using the National Aeronautics and Space Administration/Jet Propulsion Laboratory's AIRSAR L-band PolSAR imagery reveals that the proposed scheme is more effective as compared to the existing models and promises to increase the accuracy of the classification and interpretation.
机译：本文提出了一种基于极化散射相似度的极化合成孔径雷达（PolSAR）影像的​​无监督土地覆盖/土地利用分类方案。与基于显性“平均”散射机制的$ H $ / alpha分类方案相比，该方案具有以下优点：1）主要散射机制在低熵情况下代表目标散射； 2）在中熵情况下，它还代表了主要和次要的散射机制； 3）可以表示高熵情况下的所有散射机制。主要和次要散射机制已根据多重散射相似性的相对大小自动确定。对应于最大散射相似度的规范散射被认为是主要的散射机制。使用美国国家航空航天局/喷气推进实验室的AIRSAR L波段PolSAR图像获得的结果表明，与现有模型相比，该方案更有效，并有望提高分类和解释的准确性。

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