Gaussian Fitting Localization-Based SART Algorithm for 3D Particle Field Reconstruction with Single Light Field Camera

In the 3D flow field measurement technology with single light field camera, the Simultaneous Algebraic Reconstruction Technique (SART) algorithm has been widely used for the tomographic reconstruction of particle field due to its good stability and parallelism. However, the sampling angle of the single light field camera is limited and the reconstructed 3D particle field by the SART algorithm exhibits severe stretching along the depth direction within the control volume, resulting in large errors of the reconstructed particle positions and luminescence intensities. This paper proposes a Gaussian fitting localization-based SART (GFL-SART) algorithm for reconstructing the 3D particle field, which takes into account the spatial resolution of the light field camera along the depth direction and the relative size between the particle and the voxel. The GFL-SART algorithm eliminates the overlap effect of particles through the maximum between-class variance (OTSU) method and locates the true voxel position of particles by the Gaussian fitting principle during the iterative process of solving the light field tomographic reconstruction equation, and thus corrects the reconstruction result of the traditional SART algorithm. The three-dimensional particle fields generated using a pinhole array and a uniform light board were reconstructed to verify the feasibility of the proposed method. Compared with the SART algorithm, GFL-SART improves the reconstruction quality coefficient from 0.42 to about 0.99. Besides, the reconstruction time is reduced by 76.31% and the memory size of the weight matrix has been reduced by 75.67%. When the particle concentration varies between 0.20 and 0.77 ppm, the reconstruction quality coefficient of GFL-SART is always above 0.92, indicating that the proposed GFL-SART can effectively improve the stretching effect of the conventional SART algorithm with higher reconstruction quality and efficiency.