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Underwater plenoptic cameras optimized for water refraction.

Guotai Jiang, Xin Jin, Rujia Deng

|June 29, 2023

Summary

This study optimizes underwater plenoptic cameras by modeling refractive effects and developing a parameter optimization model to improve image clarity and field of view (FOV) for better 3D imaging underwater.

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Area of Science:

Optics and Photonics
Underwater Imaging Technology
Computational Imaging

Background:

Plenoptic cameras capture 3D information using microlens arrays (MLAs).
Underwater plenoptic cameras require waterproof shells, introducing refractive distortions affecting image clarity and field of view (FOV).

Purpose of the Study:

To propose an optimized underwater plenoptic camera system.
To compensate for image clarity and FOV degradation caused by underwater housing and water medium.
To ensure successful assembly and reliable 3D imaging in underwater environments.

Main Methods:

Modeling the equivalent imaging process using geometry simplification and ray propagation analysis.
Deriving an optimization model for physical parameters, including calibrating the minimum distance between the spherical shell and the main lens.
Comparing simulation results before and after underwater optimization.

Main Results:

The proposed model effectively compensates for changes in image clarity and FOV.
Simulation results confirm the correctness of the underwater optimization method.
A practical underwater focused plenoptic camera demonstrated the model's effectiveness in real-world scenarios.

Conclusions:

The developed optimization model successfully addresses the challenges of underwater plenoptic imaging.
The optimized system enhances image quality and FOV for underwater 3D reconstruction.
This research provides a viable solution for practical underwater plenoptic camera applications.