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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Improved Sigma Filter for Speckle Filtering of SAR Imagery
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Improved Sigma Filter for Speckle Filtering of SAR Imagery

机译：用于SAR图像斑点滤波的改进Sigma滤波器

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摘要

The Lee sigma filter was developed in 1983 based on the simple concept of two-sigma probability, and it was reasonably effective in speckle filtering. However, deficiencies were discovered in producing biased estimation and in blurring and depressing strong reflected targets. The advancement of synthetic aperture radar (SAR) technology with high-resolution data of large dimensions demands better and efficient speckle filtering algorithms. In this paper, we extend and improve the Lee sigma filter by eliminating these deficiencies. The bias problem is solved by redefining the sigma range based on the speckle probability density functions. To mitigate the problems of blurring and depressing strong reflective scatterers, a target signature preservation technique is developed. In addition, we incorporate the minimum-mean-square-error estimator for adaptive speckle reduction. Simulated SAR data are used to quantitatively evaluate the characteristics of this improved sigma filter and to validate its effectiveness. The proposed algorithm is applied to spaceborne and airborne SAR data to demonstrate its overall speckle filtering characteristics as compared with other algorithms. This improved sigma filter remains simple in concept and is computationally efficient but without the deficiencies of the original Lee sigma filter.
机译：Lee sigma过滤器是在1983年基于2 sigma概率的简单概念而开发的，它在散斑过滤方面相当有效。但是，在产生偏差估计以及模糊和压低强反射目标方面发现了缺陷。具有大尺寸高分辨率数据的合成孔径雷达（SAR）技术的发展需要更好，更有效的斑点滤波算法。在本文中，我们通过消除这些缺陷来扩展和改进Lee sigma滤波器。通过基于散斑概率密度函数重新定义sigma范围，可以解决偏差问题。为了减轻使强反射散射体模糊和压低的问题，开发了目标签名保存技术。此外，我们并入了最小均方误差估计器，以减少自适应斑点。模拟SAR数据用于定量评估此改进的sigma滤波器的特性并验证其有效性。将该算法应用于星载和机载SAR数据，以证明其与其他算法相比的整体散斑滤波特性。这种改进的sigma滤波器在概念上保持简单，计算效率高，但没有原始Lee sigma滤波器的缺点。

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