TL;DR
This paper introduces a compact, low-cost snapshot hyperspectral imaging system using a spectral filter array and diffuser, enabling high-resolution, rapid acquisition of spectral data without scanning.
Contribution
It presents a novel lensless computational camera design with a spectral filter array and diffuser, along with a theoretical framework and experimental validation for high-resolution hyperspectral imaging.
Findings
Achieves sub-super-pixel spatial resolution in hyperspectral images.
Demonstrates flexible spectral filter configurations for different applications.
Provides a prototype with high spatio-spectral resolution.
Abstract
Hyperspectral imaging is useful for applications ranging from medical diagnostics to agricultural crop monitoring; however, traditional scanning hyperspectral imagers are prohibitively slow and expensive for widespread adoption. Snapshot techniques exist but are often confined to bulky benchtop setups or have low spatio-spectral resolution. In this paper, we propose a novel, compact, and inexpensive computational camera for snapshot hyperspectral imaging. Our system consists of a tiled spectral filter array placed directly on the image sensor and a diffuser placed close to the sensor. Each point in the world maps to a unique pseudorandom pattern on the spectral filter array, which encodes multiplexed spatio-spectral information. By solving a sparsity-constrained inverse problem, we recover the hyperspectral volume with sub-super-pixel resolution. Our hyperspectral imaging framework is…
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