LenslessPiCam: A Hardware and Software Platform for Lensless Computational Imaging with a Raspberry Pi

• URL: http://arxiv.org/abs/2206.01430v1
• Date: Fri, 3 Jun 2022 07:39:21 GMT
• Title: LenslessPiCam: A Hardware and Software Platform for Lensless Computational Imaging with a Raspberry Pi
• Authors: Eric Bezzam, Sepand Kashani, Martin Vetterli, Matthieu Simeoni
• Abstract summary: LenslessPiCam provides a framework to enable researchers, hobbyists, and students to implement and explore lensless imaging. We provide detailed guides and exercises so that LenslessPiCam can be used as an educational resource, and point to results from our graduate-level signal processing course.
• Score: 14.690546891460235
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Lensless imaging seeks to replace/remove the lens in a conventional imaging system. The earliest cameras were in fact lensless, relying on long exposure times to form images on the other end of a small aperture in a darkened room/container (camera obscura). The introduction of a lens allowed for more light throughput and therefore shorter exposure times, while retaining sharp focus. The incorporation of digital sensors readily enabled the use of computational imaging techniques to post-process and enhance raw images (e.g. via deblurring, inpainting, denoising, sharpening). Recently, imaging scientists have started leveraging computational imaging as an integral part of lensless imaging systems, allowing them to form viewable images from the highly multiplexed raw measurements of lensless cameras (see [5] and references therein for a comprehensive treatment of lensless imaging). This represents a real paradigm shift in camera system design as there is more flexibility to cater the hardware to the application at hand (e.g. lightweight or flat designs). This increased flexibility comes however at the price of a more demanding post-processing of the raw digital recordings and a tighter integration of sensing and computation, often difficult to achieve in practice due to inefficient interactions between the various communities of scientists involved. With LenslessPiCam, we provide an easily accessible hardware and software framework to enable researchers, hobbyists, and students to implement and explore practical and computational aspects of lensless imaging. We also provide detailed guides and exercises so that LenslessPiCam can be used as an educational resource, and point to results from our graduate-level signal processing course.

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