An improved neural refractive-index-primitive method for background-oriented schlieren tomography is presented, enabling continuous three-dimensional reconstruction of refractive-index fields using a compact multilayer perceptron. The method adopts the refractive-index field as the sole neural primitive and integrates multiresolution hash encoding, automatic-discrete gradient losses, and a three-dimensional mask to enable fast convergence and high-resolution, spatially coherent reconstructions. Tests on numerical combustion phantoms and real flame data demonstrate accurate recovery of both large-scale structures and fine-scale turbulence, strong robustness to noise, and clear advantages over frequency-encoding-based and voxel-based reconstruction methods.
@article{arxiv.2605.11454,
title = {Neural Refractive Index Primitives for Flame Field Reconstruction Using Background-Oriented Schlieren},
author = {Xinyi Lu and Wei Hu and Zizhou Liao and Zheng Wang and Yue Zhang and Jingxuan Li},
journal= {arXiv preprint arXiv:2605.11454},
year = {2026}
}