A practical light transport system model for chemiluminescence distribution reconstruction

Plenoptic cameras and other integral photography instruments capture richer angular information from a scene than traditional 2D cameras. This extra information is used to estimate depth, perform superresolution or reconstruct 3D information from the scene. Many of these applications involve solving a large-scale numerical optimization problem. Most published approaches model the camera(s) using pre-computed matrices that require large amounts of memory and are not well-suited to modern many-core processors. We propose a flexible camera model based on light transport and use it to model plenoptic and traditional cameras. We implement the proposed model on a GPU and use it to reconstruct simulated and real 3D chemiluminescence distributions (flames) from images taken by traditional and plenoptic cameras.