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.

中文翻译：

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基于二维经验模态分解算法的SAR图像建筑物检测

本文提出了一种基于二维经验模式分解（BEMD）算法的合成孔径雷达（SAR）图像构建检测方法，很好地适应了非线性和非平稳信号。首先，通过BEMD算法对SAR图像进行分解，生成固有模式函数（IMFs），并结合IMFs从SAR图像中提取亮区和暗区。接下来，利用马尔可夫随机场（MRF）模型对SAR图像进行聚类，根据暗区的质心，定位具有完整边缘的暗类别。最后，通过结合亮区、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，该方法具有较高的检测精度，对中、大型、