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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Building Detection in SAR Images Based on Bi-Dimensional Empirical Mode Decomposition Algorithm
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Building Detection in SAR Images Based on Bi-Dimensional Empirical Mode Decomposition Algorithm

机译：基于双维经验模态分解算法的SAR图像中的建筑物检测

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摘要

This letter proposes a new synthetic aperture radar (SAR) image building detection method based on the bi-dimensional empirical mode decomposition (BEMD) algorithm, well adapted to nonlinear and nonstationary signals. First, the SAR image is decomposed by the BEMD algorithm to generate intrinsic mode functions (IMFs), and the IMFs are combined to extract bright regions and dark regions from the SAR image. Next, the Markov random field (MRF) model is used to cluster the SAR image, and according to the centroid of the dark region, the dark category with a complete edge is located. Finally, the building is detected by combining the bright region, the dark region, and the given shadow direction. Analytical and experimental evidence show that the proposed method has high detection accuracy and has wide applicability for medium, large, and irregular shaped buildings with shadows.
机译：这封信提出了一种基于双维经验模型分解（BEMD）算法的新的合成孔径雷达（SAR）图像构建检测方法，适用于非线性和非间断信号。首先，SAR图像由BEMD算法分解以生成内部模式功能（IMF），并且组合IMF以从SAR图像中提取亮区域和暗区。接下来，马尔可夫随机字段（MRF）模型用于聚类SAR图像，并根据暗区的质心，具有完整边缘的暗类别。最后，通过组合亮区域，暗区和给定的阴影方向来检测建筑物。分析和实验证据表明，该方法具有高检测精度，对中型，大型和不规则形状的建筑物具有广泛适用性。

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