Model-based network architecture for image reconstruction in lensless imaging

Tianjiao Zeng; Edmund Y. Lam

doi:10.1117/12.2575205

10 October 2020 Model-based network architecture for image reconstruction in lensless imaging

Tianjiao Zeng, Edmund Y. Lam

Proceedings Volume 11551, Holography, Diffractive Optics, and Applications X; 115510B (2020) https://doi.org/10.1117/12.2575205
Event: SPIE/COS Photonics Asia, 2020, Online Only

Abstract

We introduce a multi-branch model-based architecture for image reconstruction in lensless imaging. The structure consists of two learning branches, namely a physical model-based network, and a data-driven network. It uses intermediate outputs from the former as a prior for guiding the learning of the reconstruction neural network, which mimics the mapping between the reconstructed high-resolution images and raw images. We demonstrate that the proposed architecture offers a flexible combination of model-based methods and deep networks with superior reconstruction performance than methods using only an unrolled optimization network or pure deep neural networks for image reconstruction.

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Citation Download Citation

Tianjiao Zeng and Edmund Y. Lam "Model-based network architecture for image reconstruction in lensless imaging", Proc. SPIE 11551, Holography, Diffractive Optics, and Applications X, 115510B (10 October 2020); https://doi.org/10.1117/12.2575205

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