A progressive error estimation framework for photon density estimation
ACM SIGGRAPH Asia 2010 papers
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We present an adaptive noise reduction technique for progressive photon mapping, which preserves the consistency of the original algorithm. Although progressive photon mapping converges to the correct result in the limit, the image produced after a finite number of samples can suffer from both bias and noise [Hachisuka et al. 2010]. The bias can be seen as blurry lighting features while the noise can be seen as splotches.