Spectral Gradient Sampling for Path Tracing

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dc.contributor.authorPetitjean, Victoren_US
dc.contributor.authorBauszat, Pabloen_US
dc.contributor.authorEisemann, Elmaren_US
dc.contributor.editorJakob, Wenzel and Hachisuka, Toshiyaen_US
dc.date.accessioned2018-07-01T07:22:35Z
dc.date.available2018-07-01T07:22:35Z
dc.date.issued2018
dc.description.abstractSpectral Monte-Carlo methods are currently the most powerful techniques for simulating light transport with wavelengthdependent phenomena (e.g., dispersion, colored particle scattering, or diffraction gratings). Compared to trichromatic rendering, sampling the spectral domain requires significantly more samples for noise-free images. Inspired by gradient-domain rendering, which estimates image gradients, we propose spectral gradient sampling to estimate the gradients of the spectral distribution inside a pixel. These gradients can be sampled with a significantly lower variance by carefully correlating the path samples of a pixel in the spectral domain, and we introduce a mapping function that shifts paths with wavelength-dependent interactions. We compute the result of each pixel by integrating the estimated gradients over the spectral domain using a onedimensional screened Poisson reconstruction. Our method improves convergence and reduces chromatic noise from spectral sampling, as demonstrated by our implementation within a conventional path tracer.en_US
dc.description.number4
dc.description.sectionheadersRendering Techniques I
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume37
dc.identifier.doi10.1111/cgf.13474
dc.identifier.issn1467-8659
dc.identifier.pages45-53
dc.identifier.urihttps://doi.org/10.1111/cgf.13474
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13474
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies → Ray tracing
dc.titleSpectral Gradient Sampling for Path Tracingen_US
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