Photorealistic Image Rendering with Population Monte Carlo Energy Redistribution

This work presents a novel global illumination algorithm which concentrates computation on important light transport paths and automatically adjusts energy distributed area for each light transport path. We adapt statistical framework of Population Monte Carlo into global illumination to improve rendering efficiency. Information collected in previous iterations is used to guide subsequent iterations by adapting the kernel function to approximate the target distribution without introducing bias into the final result. Based on this framework, our algorithm automatically adapts the amount of energy redistribution at different pixels and the area over which energy is redistributed. Our results show that the efficiency can be improved by exploring the correlated information among light transport paths.

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