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Description

Hyperspectral imaging (HSI) is an imaging technique that captures the spectral response for every point in the scene. It has application is remote sensing, agriculture, medical imaging, and fluorescence microscopy. A number of these applications require a snapshot HSI system with high acquisition speeds. However, most of these snapshot systems are either too bulky and expensive, or they require a custom fabrication process. This results in reduced accessibility to these systems due to price, long lead times, and lack of access to custom fabrication tools. We use a compact snapshot HSI system (Spectral Diffuserscope) as a reference to propose alternative designs that are simpler to reproduce.

In this work we present two designs for computational snapshot HSI systems which are simple to fabricate. They can both be fabricated in lab using mostly off-the-shelf components. This makes the system easier to reproduce and allows us to use an imaging sensor of our choice as part of our HSI system.

For the first design, we outline a detailed fabrication and calibration procedure. Additionally, we discuss appropriate computational modifications to improve reconstruction fidelity. We show initial experimental results to show how these modifications help improve reconstructions. We also discuss how to adapt the system for coupling into a benchtop microscope.

For the second design, we again outline a detailed fabrication and calibration procedure. We present initial simulation results to aid the design process if the system were to be fabricated. We briefly discuss the important design tradeoffs associated with this system and the possibilities of extending this work in the future.

Details

Title
Exploring alternative designs for a computational hyperspectral imager for microscopy
Creator
Raniwala, Yashovardhan, Author
Published
EECS Department, University of California at Berkeley, Berkeley, California, 05/10/23
Full Collection Name
Electrical Engineering & Computer Sciences Technical Reports
Other Identifiers
EECS-2023-82
Type
Text
Format
technical reports
Extent
54 p
Language
eng
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