Stochastic Texture Filtering

• URL: http://arxiv.org/abs/2305.05810v2
• Date: Mon, 15 May 2023 14:17:55 GMT
• Title: Stochastic Texture Filtering
• Authors: Marcos Fajardo, Bartlomiej Wronski, Marco Salvi, Matt Pharr
• Abstract summary: Filtered texture lookups are integral to producing high-quality imagery. We show that filtering after evaluating lighting, rather than before BSDF evaluation as is current practice, gives a more accurate solution to the rendering equation. We demonstrate applications in both real-time and offline rendering and show that the additional error is minimal.
• Score: 3.4202659118354104
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: 2D texture maps and 3D voxel arrays are widely used to add rich detail to the surfaces and volumes of rendered scenes, and filtered texture lookups are integral to producing high-quality imagery. We show that filtering textures after evaluating lighting, rather than before BSDF evaluation as is current practice, gives a more accurate solution to the rendering equation. These benefits are not merely theoretical, but are apparent in common cases. We further show that stochastically sampling texture filters is crucial for enabling this approach, which has not been possible previously except in limited cases. Stochastic texture filtering offers additional benefits, including efficient implementation of high-quality texture filters and efficient filtering of textures stored in compressed and sparse data structures, including neural representations. We demonstrate applications in both real-time and offline rendering and show that the additional stochastic error is minimal. Furthermore, this error is handled well by either spatiotemporal denoising or moderate pixel sampling rates.

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