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Multimodal Optical Imaging Platform for Studying Cellular Metabolism

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Shared-modality multi-bandpass filtering for plug-and-play multispectral depth imaging.

Zhiwei Deng, Zhan Shi, Shiqiao Li

|July 30, 2025

Summary

This summary is machine-generated.

We introduce a shared-modality multi-bandpass filtering (SMF) method for multispectral depth imaging (MDI). This technique simplifies spectral and depth registration, enabling more compact and efficient imaging systems.

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Area of Science:

Optics and Photonics
Computer Vision
Robotics

Background:

Traditional multispectral filter array (MFA) cameras require precise pixel-level alignment.
Conventional parallel systems for multispectral depth imaging (MDI) necessitate cross-modal registration.
Existing systems can be bulky and complex due to alignment requirements.

Purpose of the Study:

To propose a novel shared-modality multi-bandpass filtering (SMF) method for plug-and-play MDI.
To enable flexible, customizable, and cost-effective multispectral imaging.
To develop a system with simplified registration and reduced volume.

Main Methods:

Utilized a low-cost planar multi-bandpass (MBP) filter for spectral filtering.
Implemented real-time linear computation for image processing.
Integrated batch-fabricated MBPs across parallel cameras for shared-modal registration.

Main Results:

Developed a prototype system with two SMF cameras for real-time 7-band spectral and depth imaging.
Achieved 10-15 nm spectral full width at half maximum (FWHM).
Demonstrated 1.75 mm depth accuracy at 1600 × 1300 spatial resolution and 30 fps.

Conclusions:

The SMF method offers a simplified and more compact approach to MDI.
The prototype system effectively performs real-time spectral and depth imaging.
The technology is validated for practical applications like autonomous driving.