Consistent Post-Reconstruction for Progressive Photon Mapping
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Date
2021
Authors
Journal Title
Journal ISSN
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Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
Photon mapping is a light transport algorithm that simulates various rendering effects (e.g., caustics) robustly, and its progressive variants, progressive photon mapping (PPM) methods, can produce a biased but consistent rendering output. PPM estimates radiance using a kernel density estimation whose parameters (bandwidths) are adjusted progressively, and this refinement enables to reduce its estimation bias. Nonetheless, many iterations (and thus a large number of photons) are often required until PPM produces nearly converged estimates. This paper proposes a post-reconstruction that improves the performance of PPM by reducing residual errors in PPM estimates. Our key idea is to take multiple PPM estimates with multi-level correlation structures, and fuse the input images using a weight function trained by supervised learning with maintaining the consistency of PPM. We demonstrate that our technique boosts an existing PPM technique for various rendering scenes.
Description
@article{10.1111:cgf.14406,
journal = {Computer Graphics Forum},
title = {{Consistent Post-Reconstruction for Progressive Photon Mapping}},
author = {Choi, Hajin and Moon, Bochang},
year = {2021},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.14406}
}