Efficient reconstruction of holographic lens-free images by sparse phase recovery

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Abstract

Digital holographic lens-free imaging is based on recording the diffraction pattern of light after it passes through a specimen and post-processing the recorded diffraction pattern to reconstruct an image of the specimen. If the full, complex-valued wave-front of the diffraction pattern could be recorded then the image reconstruction process would be straight-forward, but unfortunately image sensors typically only record the amplitude of the diffraction pattern but not the phase. As a result, many conventional reconstruction techniques suffer from substantial artifacts and degraded image quality. This paper presents a computationally efficient technique to reconstruct holographic lens-free images based on sparsity, which improves image quality over existing techniques, allows for the possibility of reconstructing images over a 3D volume of focal-depths simultaneously from a single recorded hologram, provides a robust estimate of the missing phase information in the hologram, and automatically identifies the focal depths of the imaged objects in a robust manner.

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Haeffele, B. D., Stahl, R., Vanmeerbeeck, G., & Vidal, R. (2017). Efficient reconstruction of holographic lens-free images by sparse phase recovery. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10434 LNCS, pp. 109–117). Springer Verlag. https://doi.org/10.1007/978-3-319-66185-8_13

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