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3D localization of point source based on light field imaging and deep learning

机译:基于光场成像和深度学习的点源3D定位

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3D localization of point source is widely used in many fields, such as bioimaging and autonomous driving fields.However, the localization is hard to perform under scattering conditions because of the diffuse effect of the scattering.We propose a novel method for 3D localization of point source under scattering conditions based on light field imagingand deep learning by only one shot. First, we introduce the description of the point source in a light field wise and how tolocalize a point source by its light field. On the basis, we elaborate on the effect of scattering on a light field and how toretrieve the location of a point source from a light field with scattering. Then, the effect of aberration on a light field willbe introduced. We also build an artificial scene and a deep learning framework to perform a 3D localization practically,and the feasibility and accuracy of our method have been evaluated.
机译:点源的3D定位已广泛应用于许多领域,例如生物成像和自动驾驶领域。 但是,由于散射的扩散效应,在散射条件下难以进行定位。 我们提出了一种基于光场成像的散射条件下点源3D定位的新方法 一键深度学习。首先,我们在光场方面介绍点光源的描述以及如何 通过其光场定位点光源。在此基础上,我们详细阐述了散射对光场的影响以及如何 从具有散射的光场中获取点光源的位置。然后,像差对光场的影响将 被介绍。我们还构建了人工场景和深度学习框架,以实际执行3D本地化, 并对我们方法的可行性和准确性进行了评估。

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