BOS/schlieren synthetic image generation via MIRAGE (MATLAB implementation of ray tracing for analysis of variable density Gradient Environments)
Year: 2026
Type: article
Abstract: This work presents a MATLAB-based, open source tool for generating synthetic images, e.g. background oriented schlieren (BOS), in non-homogeneous refractive index field environments induced by the presence of density gradients. The tool allows the user model their specific optical setup and input a known flow density field (e.g. from CFD simulations) to generate experiment-like images using geometric ray tracing. MIRAGE (MATLAB Implementation of Ray tracing for Analysis of variable density Gradient Environments) can be used by researchers for designing experiments and assessing post-processing schemes, error analyses, and uncertainty quantification models. The simulation begins by initializing light rays from the light source or background pattern. The light rays are then propagated through the user-defined optical components and density gradient field before intensity is accumulated at the camera sensor plane using a cosine-fourth-power law and bilinear weighting scheme. Ray tracing through the density gradient field is performed using a fourth order Runge–Kutta scheme and is validated using a simulation of a Luneberg lens. The entire program is also validated by generating a synthetic BOS image using CFD data of a low Mach number turbulent mixing layer. The density gradients calculated from the synthetic BOS image are in good qualitative and quantitative agreement with the CFD span-averaged density gradients. The entire program is housed in a graphical user interface (GUI), making it easy and intuitive for the user to conduct simulations using their own datasets and experimental setups.
Institutions: Purdue University West Lafayette, Purdue University System
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,325
OpenAlex ID: W7134809557
