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A Learning Approach to Compressive Holography

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Abstract

Compressive holography enables 3D tomographic reconstruction from 2D holographic data. We approach the holography task by solving a nonlinear inverse model, formulated from the Iterative Born Approximation (IBA), using error-backpropagation in a feedforward neural network.

© 2017 Optical Society of America

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