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On the role of non-local filtering in forest vertical structure characterization using SAR tomography

机译:SAR层析成像非局部滤波在森林垂直结构表征中的作用

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SAR tomography (TomoSAR) allows facing the problem related to the interference of coherent scatterers within the same pixels due to the occurrence of layover. Whereas, full imaging the continuous reflectivity profile along the elevation dimension is a typical framework to deal with the non-coherent volumetric scatterers in the forested area. Layover usually arises in volumetric scenario and leads to discontinuity in the reconstructed vertical reflectivity image. This paper aims to investigate the possibility of addressing layover issue in forested area by exploiting the unified non-local (NL) filtering of multi-baseline (MB) covariance matrix. To this aim, the performance of non-parametric Capon spectral estimation technique has been analyzed using the NL filtered MB covariance matrix and efficient vertical reflectivity profile reconstruction is demonstrated, which almost addressed the layover issues.
机译:SAR层析成像(TomoSAR)允许面对与由于发生重叠而在相同像素内的相干散射体的干扰有关的问题。而沿海拔高度方向对连续反射率剖面进行完整成像是处理林区中非相干体积散射体的典型框架。重叠通常发生在体积场景中,并导致重建的垂直反射率图像不连续。本文旨在通过利用多基线(MB)协方差矩阵的统一非局部(NL)过滤来研究解决林区中的中转问题的可能性。为此,已使用NL滤波MB协方差矩阵分析了非参数Capon光谱估计技术的性能,并证明了有效的垂直反射率轮廓重建,几乎解决了中转问题。

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