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Three-dimensional computational holographic imaging and recognition using independent component analysis

机译:使用独立分量分析的三维计算全息成像和识别

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摘要

We present computational holographic three-dimensional imaging and automated object recognition based on independent component analysis (ICA). Three-dimensional sensing of the scene is performed by computational holographic imaging of the objects using phase-shifting digital holography. We used principal components analysis to reduce data dimension and ICA to recognize the three-dimensional objects. In this paper, kurtosis maximization-based algorithm is used. To the best of our knowledge, this paper is the first to report using ICA in three-dimensional imaging technology.
机译:我们提出基于独立成分分析(ICA)的计算全息三维成像和自动对象识别。场景的三维感测是通过使用相移数字全息术对物体进行计算全息照相来实现的。我们使用主成分分析来减少数据维,并使用ICA来识别三维对象。在本文中,使用了基于峰度最大化的算法。据我们所知,本文是第一个报告在三维成像技术中使用ICA的报告。

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