Fast Final Gathering via Reverse Photon Mapping

We present a new algorithm for computing indirect illumination based on density estimation similarly to photon mapping. We accelerate the search for final gathering by reorganizing the computation in the reverse order. We use two trees that organize spatially not only the position of photons but also the position of final gather rays. The achieved speedup is algorithmic, the performance improvement takes advantage of logarithmic complexity of searching in trees. The algorithm requires almost no user settings unlike many known acceleration techniques for photon mapping. The image quality is the same as for traditional photon mapping with final gathering, since the algorithm does not approximate or interpolate. Optionally, the algorithm can be combined with other techniques such as density control and importance sampling. The algorithm creates a coherent access pattern to the main memory. This further improves on performance and also allows us to use efficient external data structures to alleviate the increasedmemory requirements.