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Wavelets, Curvelets and Multiresolution Analysis Techniques Applied to Implosion Symmetry Characterization of ICF Targets

机译:应用于ICF目标的爆炸对称表征的小波,曲线和多分辨率分析技术

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We introduce wavelets, curvelets and multiresolution analysis techniques to assess the symmetry of X ray driven imploding shells in ICF targets. After denoising X ray backlighting produced images, we determine the Shell Thickness Averaged Radius (STAR) of maximum density, r~*(N, θ), where N is the percentage of the shell thickness over which to average. The non-uniformities of r~*(N, θ) are quantified by a Legendre polynomial decomposition in angle, θ. Undecimated wavelet decompositions outperform decimated ones in denoising and both are surpassed by the curvelet transform. In each case, hard thresholding based on noise modeling is used. We have also applied combined wavelet and curvelet filter techniques with variational minimization as a way to select the significant coefficients. Gains are minimal over curvelets alone in the images we have analyzed.
机译:我们引入小波,曲线和多分辨率分析技术,以评估ICF目标中X射线驱动爆炸壳的对称性。 在去噪X射线背光产生的图像后,我们确定最大密度的壳厚度(星),R〜*(n,θ),其中n是平均值的壳体厚度的百分比。 R〜*(n,θ)的非均匀性通过角度θ,θ的图例多项式分解量化。 未定义的小波分解在弯曲和两者上倾向于弯曲的小波分解。 在每种情况下,使用基于噪声建模的硬阈值。 我们还应用了组合小波和曲线滤波器技术,具有变分的最小化作为选择显着系数的方法。 在我们分析的图像中,收益在曲视上是最小的。

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