• Journal of the Korea Computer Graphics Society
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• v.16 no.3
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• pp.41-48
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• 2010

Photon mapping is a traditional global illumination method using many photons emitted from the light source for photo-realistic rendering. However, this method needs a lot of resources to perform tracing of millions of photons. Progressive photon mapping solves this problem. Typical progressive photon mapping performs ray tracing at first to find the hit points on diffuse surface of objects. Next, light source repeatedly emits a small number of photons in photon tracing pass, and power of photons in each sphere that has a fixed radius with the hit points in the center is accumulated. This method requires less resources than previous photon mapping, but it spends much time for gathering enough photons since each of photons progresses through a random direction and rendering high quality image. To improve the method, we propose photon probing that calculates variance of photons in the sphere and controls radius of sphere. In addition, we apply cone filter in radiance estimation step for reducing aliasing at the edges in result image.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.141-147
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• 2024

Progressive photon mapping is a widely adopted rendering technique that conducts a kernel-density estimation on photons progressively generated from lights. Its hyperparameter, which controls the reduction rate of the density estimation, highly affects the quality of its rendering image due to the bias-variance tradeoff of pixel estimates in photon-mapped results. We can minimize the errors of rendered pixel estimates in progressive photon mapping by estimating the optimal parameters based on gradient-based optimization techniques. To this end, we derived the gradients of pixel estimates with respect to the parameters when performing progressive photon mapping and compared our estimated gradients with finite differences to verify estimated gradients. The gradient estimated in this paper can be applied in an online learning algorithm that simultaneously performs progressive photon mapping and parameter optimization in future work.