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arXiv · 2403.00537

A Modular and Robust Physics-Based Approach for Lensless Image Reconstruction

Yohann Perron·Eric Bezzam·Martin Vetterli
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Abstract

In this paper, we present a modular approach for reconstructing lensless measurements. It consists of three components: a newly-proposed pre-processor, a physics-based camera inverter to undo the multiplexing of lensless imaging, and a post-processor. The pre- and post-processors address noise and artifacts unique to lensless imaging before and after camera inversion respectively. By training the three components end-to-end, we obtain a 1.9 dB increase in PSNR and a 14% relative improvement in a perceptual image metric (LPIPS) with respect to previously proposed physics-based methods. We also demonstrate how the proposed pre-processor provides more robustness to input noise, and how an auxiliary loss can improve interpretability.

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Yohann Perron, Eric Bezzam, Martin Vetterli. 2024-03-01. A Modular and Robust Physics-Based Approach for Lensless Image Reconstruction. https://arxiv.org/abs/2403.00537

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