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首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Unsupervised Estimation of the Equivalent Number of Looks in SAR Images
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Unsupervised Estimation of the Equivalent Number of Looks in SAR Images

机译：SAR图像中等效视数的无监督估计

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摘要

In this letter, an unsupervised method for estimating the equivalent number of looks (ENL) in synthetic aperture radar (SAR) images is proposed. Assuming that the multiplicative noise in the SAR images is a unit mean random variable of Gamma distribution parameterized by the ENL, a lookup table between the ENL and the variance of the logarithm of the multiplicative noise is established. Then, for a SAR image, we first apply the logarithmic transform to make the multiplicative noise become additive. After that, the variance of the additive noise in the logarithmic image is estimated; finally, the ENL is obtained according to the estimated noise variance by the pre-established lookup table. The effectiveness of the proposed method is demonstrated with both simulated and real SAR images.
机译：在这封信中，提出了一种用于估计合成孔径雷达（SAR）图像中等效视线数（ENL）的无监督方法。假设SAR图像中的乘法噪声是由ENL参数化的伽马分布的单位均值随机变量，则在ENL与乘法噪声的对数的方差之间建立查找表。然后，对于SAR图像，我们首先应用对数变换使乘性噪声成为可加性。之后，估计对数图像中附加噪声的方差；最后，根据预先建立的查找表根据估计的噪声方差获得ENL。模拟和真实SAR图像都证明了该方法的有效性。

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