Remote Sensing, Vol. 16, Pages 2429: Optical Imaging Model Based on GPU-Accelerated Monte Carlo Simulation for Deep-Sea Luminescent Objects

Remote Sensing, Vol. 16, Pages 2429: Optical Imaging Model Based on GPU-Accelerated Monte Carlo Simulation for Deep-Sea Luminescent Objects

Remote Sensing doi: 10.3390/rs16132429

Authors: Qing Han Mengnan Sun Bing Zheng Min Fu

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.