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We introduce a reconstruction algorithm that generates a temporally stable sequence of images from one path-per-pixel global illumination. To handle such noisy input, we use temporal accumulation to increase the effective sample count and spatiotemporal luminance variance estimates to drive a hierarchical, image-space wavelet filter [Dammertz et al. 2010]. This hierarchy allows us to distinguish between noise and detail at multiple scales using local luminance variance.

Physically based light transport is a long-standing goal for realtime computer graphics. While modern games use limited forms of ray tracing, physically based Monte Carlo global illumination does not meet their 30 Hz minimal performance requirement. Looking ahead to fully dynamic real-time path tracing, we expect this to only be feasible using a small number of paths per pixel. As such, image reconstruction using low sample counts is key to …