Hyperpixels: Pixel Filter Arrays of Multivariate Optical Elements for Optimized Spectral Imaging
arxiv(2024)
摘要
We introduce the concept of `hyperpixels' in which each element of a pixel
filter array (suitable for CMOS image sensor integration) has a spectral
transmission tailored to a target spectral component expected in
application-specific scenes. These are analogous to arrays of multivariate
optical elements that could be used for sensing specific analytes. Spectral
tailoring is achieved by engineering the heights of multiple sub-pixel
Fabry-Perot resonators that cover each pixel area. We first present a design
approach for hyperpixels, based on a matched filter concept and, as an
exemplar, design a set of 4 hyperpixels tailored to optimally discriminate
between 4 spectral reflectance targets. Next, we fabricate repeating 2x2 pixel
filter arrays of these designs, alongside repeating 2x2 arrays of an optimal
bandpass filters, perform both spectral and imaging characterization.
Experimentally measured hyperpixel transmission spectra show a 2.4x reduction
in unmixing matrix condition number (p=0.031) compared to the optimal band-pass
set. Imaging experiments using the filter arrays with a monochrome sensor
achieve a 3.47x reduction in unmixing matrix condition number (p=0.020)
compared to the optimal band-pass set. This demonstrates the utility of the
hyperpixel approach and shows its superiority even over the optimal bandpass
case. We expect that with further improvements in design and fabrication
processes increased performance may be obtained. Because the hyperpixels are
straightforward to customize, fabricate and can be placed atop monochrome
sensors, this approach is highly versatile and could be adapted to a wide range
of real-time imaging applications which are limited by low SNR including
micro-endoscopy, capsule endoscopy, industrial inspection and machine vision.
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