Reconstructing Synthetic Lensless Images in the Low-Data Regime

Abeer Banerjee (CSIR-CEERI),* Himanshu Kumar (CSIR-CEERI), Sumeet Saurav (CSIR-CEERI), Sanjay Singh (CSIR-CEERI, Pilani )
The 34th British Machine Vision Conference


Lensless image reconstruction is a class of inverse problems in computational imaging that is gaining immense popularity in the imaging research community because of its potential to revolutionize traditional imaging systems radically. It is possible to build cameras with extremely flat form factors that enable imaging in challenging scenarios. In this paper, we reconstruct simulated lensless images using a very low number of examples where we pre-train a decoder architecture with the available examples to model the data semantics, and then solve the inverse problem of lensless image reconstruction guided by a physics-informed forward loss function. We contrastively analyze and evaluate the reconstruction performance of our model against its untrained counterpart and show a substantial improvement in the reconstruction quality and convergence time even with a few example images.



author    = {Abeer Banerjee and Himanshu Kumar and Sumeet Saurav and Sanjay  Singh},
title     = {Reconstructing Synthetic Lensless Images in the Low-Data Regime},
booktitle = {34th British Machine Vision Conference 2023, {BMVC} 2023, Aberdeen, UK, November 20-24, 2023},
publisher = {BMVA},
year      = {2023},
url       = {}

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