Microlocal Analysis of the Geometric Separation Problem
Microlocal Analysis of the Geometric Separation Problem
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DOI：
10.1002/cpa.21418
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发表时间：
2010-04
影响因子：
3
通讯作者：
D. Donoho;Gitta Kutyniok
中科院分区：
文献类型：
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作者：
D. Donoho;Gitta Kutyniok
图像数据通常由两个或多个几何上不同的成分组成；例如，在星系目录中，人们会看到点状结构（星系超星系团）和曲线状结构（细丝）的混合体。理想的情况是处理单个图像并提取两个几何“纯”图像，每个图像仅包含两个几何成分之一的特征。这似乎是一个严重未确定的问题，但最近的实证研究取得了极具说服力的分离。
Image data are often composed of two or more geometrically distinct constituents; in galaxy catalogs, for instance, one sees a mixture of pointlike structures (galaxy superclusters) and curvelike structures (filaments). It would be ideal to process a single image and extract two geometrically “pure” images, each one containing features from only one of the two geometric constituents. This seems to be a seriously underdetermined problem but recent empirical work achieved highly persuasive separations.