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Depth-independent segmentation of macroscopic three-dimensional objects encoded in single perspectives of digital holograms

机译:在数字全息图的单一视角下编码的宏观三维对象的深度无关分割

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摘要

We present a technique for performing segmentation of macroscopic three-dimensional objects recorded using in-line digital holography. We numerically reconstruct a single perspective of each object at a range of depths. At each point in the digital wavefront we calculate variance about a neighborhood. The maximum variance at each point over all depths is thresholded to classify it as an object pixel or a background pixel. Segmentation results for objects of low and high contrast are presented.
机译:我们提出了一种技术,用于对使用在线数字全息术记录的宏观三维物体进行分割。我们在一定深度范围内以数字方式重建每个对象的单个透视图。在数字波阵面的每个点上,我们都会计算邻域的方差。将所有深度上每个点的最大方差设置为阈值,以将其分类为对象像素或背景像素。给出了低对比度和高对比度对象的分割结果。

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