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Evaluating an adaptive windowing scheme in speckle noise MAP filtering

机译:评估Speckle噪声映射滤波中的自适应窗口方案

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Synthetic aperture radar (SAR) images are corrupted by speckle noise, which degrades the quality and interpretation of the images. Speckle removal provides a better interpretability of SAR images if the technique performs the filtering without loss of spatial resolution and preserves fine details and edges. This work aims to redefine the neighborhood areas around the noisy pixel and in this area the local mean and variance are computed to estimate the Maximum a Posteriori (MAP) filter parameters. The proposed modified MAP algorithm improves the ability to filter the speckle noise without blurring edges and targets by applying the MAP estimator in the current adaptive window that is controlled by a measure of homogeneity in the area around the noisy pixel. This adaptive windowing was also incorporated to the classical Kuan [3] and Frost [13] filters in order to evaluate the performance of the proposed scheme. The effectiveness in reducing speckle by the modified MAP filter is evaluated in terms of qualitative and quantitative aspects such as line and edge preservation and the improvement of the signal to noise ratio. The tests were performed in real SAR images.
机译:合成孔径雷达(SAR)图像被散斑噪声损坏,从而降低了图像的质量和解释。如果该技术在不损失空间分辨率并保留精细细节和边缘的情况下,则散斑拆卸提供了SAR图像的更好的解释性。这项工作旨在重新定义嘈杂像素周围的邻居区域,并且在该区域中,计算局部均值和方差以估计最大后验(MAP)滤波器参数。所提出的修改的MAP算法通过在当前自适应窗口中应用由噪声围绕噪声像素周围的区域中的均匀性的均匀性来控制的当前自适应窗口中的MAP估计来改善无需模糊的散斑噪声的能力。这种自适应窗口也被纳入了经典的kuan [3]和霜[13]过滤器,以评估所提出的方案的性能。根据定性和定量方面,如线和边缘保存等定量和定量方面评估了修改的地图过滤器的散斑的有效性以及信号到噪声比的改善。测试是在真实的SAR图像中进行的。

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