Laser De-Bayering of Low-Cost Image Sensors

Publisher: IEEE

Abstract:Building upon prior work, a novel laser stripping method for removing the Bayer layer from an inexpensive back-illuminated complementary metal–oxide semiconductor image s...View more
Abstract:
Building upon prior work, a novel laser stripping method for removing the Bayer layer from an inexpensive back-illuminated complementary metal–oxide semiconductor image sensor (Raspberry Pi camera) is disclosed. The laser stripping process provides an attractive alternative to chemical stripping, negating the requirement for the processing of such sensors with harmful and environmentally damaging chemicals. Additionally, the method disclosed, though limited in speed, lays the groundwork toward a potentially fast and scalable process. It is demonstrated that such sensors, when stripped of the Bayer layer, exhibit enhanced spectral resolution and range from the ultraviolet to the infrared. Such inexpensive camera sensors, once modified, may be suitable for a variety of scientific applications where a high-resolution, broad spectral response is required, for example, in compact optical spectrometers.
Published in: IEEE Sensors Letters ( Volume: 7, Issue: 1, January 2023)
Article Sequence Number: 3500104
Date of Publication: 26 December 2022
Electronic ISSN: 2475-1472
Publisher: IEEE

I. Introduction

Recently, a means of removing the Bayer filter layer from low-cost, readily available Smart Phone [complementary metal–oxide semiconductor (CMOS)] sensors (Raspberry Pi cameras) rendering them sensitive to ultraviolet (UV) light has been discussed in the literature. The de-Bayering of camera sensors described in this prior work is a wet chemical process using Posistrip EKC830 to strip the Bayer layer and microlenses from the surface of the CMOS sensor, yielding a camera sensor with a significantly extended spectral response, specifically into the UV, as low as 310 nm. Such de-Bayered cameras may offer a low-cost imaging solution for a variety of applications, such as UV imaging for measuring Sulfur Dioxide emissions in atmospheric science or volcanology [1].

References

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