Optical Imaging Model Based on GPU-Accelerated Monte Carlo Simulation for Deep-Sea Luminescent Objects

Modeling and simulating the underwater optical imaging process can assist in optimizing the configuration of underwater optical imaging technology. Based on the Monte Carlo (MC) method, we propose an optical imaging model which is tailored for deep-sea luminescent objects. Employing GPU parallel acc...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2024-07, Vol.16 (13), p.2429
Main Authors: Han, Qing, Sun, Mengnan, Zheng, Bing, Fu, Min
Format: Article
Language:English
Subjects:
Acceleration
Acoustics
Atoms & subatomic particles
Boundary conditions
Cameras
Deep sea
Deep sea environments
GPU acceleration
Image processing
Imaging
Lenses
Light
Methods
Monte Carlo
Monte Carlo simulation
Optical properties
Propagation
Ray tracing
Underwater
underwater optical imaging
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Summary:Modeling and simulating the underwater optical imaging process can assist in optimizing the configuration of underwater optical imaging technology. Based on the Monte Carlo (MC) method, we propose an optical imaging model which is tailored for deep-sea luminescent objects. Employing GPU parallel acceleration expedites the speed of MC simulation and ray-tracing, achieving a three-order-of-magnitude speedup over a CPU-based program. A deep-sea single-lens imaging system is constructed in the model, composed of a luminescent object, water medium, double-convex lens, aperture diaphragm, and sensor. The image of the luminescent object passing through the imaging system is generated using the forward ray-tracing method. This model enables an intuitive analysis of the inherent optical properties of water and imaging device parameters, such as sensor size, lens focal length, field of view (FOV), and camera position on imaging outcomes in the deep-sea environment.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs16132429