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Change detection in polarimetric SAR images using complex Wishart distributed matrices

机译:利用复杂的Wishart分布矩阵改变极化saR图像的检测

摘要

In surveillance it is important to be able to detect natural or man-made changes e.g. based on sequences of satellite or air borne images of the same area taken at different times. The mapping capability of synthetic aperture radar (SAR) is independent of e.g. cloud cover, and thus this technology holds a strong potential for change detection studies in remote sensing. In polarimetric synthetic aperture radar we measure the amplitude and phase of backscattered signals in four combinations of the linear horizontal and vertical receive and transmit polarizations. These signals form a complex scattering matrix, and after suitable preprocessing the outcome at each picture element (pixel) may be represented as a 3 by 3 Hermitian matrix following a complex Wishart distribution. One approach to solving the change detection problem based on SAR images is therefore to apply suitable statistical tests in the complex Wishart distribution. We propose a set-up for a systematic solution to the (practical) problems using the likelihood ratio test statistics. We show some examples based on a time series of images with 1024 by 1024 pixels.
机译:在监视中,重要的是能够检测自然或人为的变化,例如基于在不同时间拍摄的同一区域的卫星或空中图像序列。合成孔径雷达(SAR)的制图能力独立于例如云覆盖,因此该技术在遥感变化检测研究中具有强大的潜力。在极化合成孔径雷达中,我们以线性水平和垂直接收和发射极化的四个组合来测量反向散射信号的幅度和相位。这些信号形成一个复杂的散射矩阵,经过适当的预处理后,每个像素(像素)处的结果可以表示为遵循复杂Wishart分布的3 x 3 Hermitian矩阵。因此,解决基于SAR图像的变化检测问题的一种方法是在复杂的Wishart分布中应用适当的统计检验。我们提出一种使用似然比检验统计量系统解决(实际)问题的方案。我们显示了一些基于1024 x 1024像素的图像时间序列的示例。

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