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Rendering Along the Hilbert Curve

In: Advances in Modeling and Simulation

Author

Listed:
  • Alexander Keller

    (NVIDIA)

  • Carsten Wächter

    (NVIDIA)

  • Nikolaus Binder

    (NVIDIA)

Abstract

Based on the seminal work on Array-RQMC methods and rank-1 lattice sequences by Pierre L’Ecuyer and collaborators, we introduce efficient deterministic algorithms for image synthesis. Enumerating a low discrepancy sequence along the Hilbert curve superimposed on the raster of pixels of an image, we achieve noise characteristics that are desirable with respect to the human visual system, especially at very low sampling rates. As compared to the state of the art, our simple algorithms neither require randomization, nor costly optimization, nor lookup tables. We analyze correlations of space-filling curves and low discrepancy sequences, and demonstrate the benefits of the new algorithms in a professional, massively parallel light transport simulation and rendering system.

Suggested Citation

  • Alexander Keller & Carsten Wächter & Nikolaus Binder, 2022. "Rendering Along the Hilbert Curve," Springer Books, in: Zdravko Botev & Alexander Keller & Christiane Lemieux & Bruno Tuffin (ed.), Advances in Modeling and Simulation, pages 319-332, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-10193-9_16
    DOI: 10.1007/978-3-031-10193-9_16
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