Texture Space Shading for Ray Tracing Noise Reduction
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Solution Overview
Problem
Existing ray tracing techniques are costly in terms of memory, computations, and power, and struggle with noise removal, camera effects, and visibility discontinuities, limiting the feasibility of high-quality real-time rendering.
Innovation Solution
A novel approach that performs sampling and filtering directly in texture space, caching and reusing shaded texels, and applying simpler filters to efficiently handle camera effects and reduce memory footprint.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If ray tracing is used to generate realistic images, then image quality is improved, but computational cost and memory usage increase significantly
Solution Approach 1:
The patent segments the rendering process into distinct phases: primary ray tracing, guide image generation, and texture space filtering. By dividing the computational workload and processing different ray types separately, the system manages complexity while maintaining image quality. The segmentation allows efficient reuse of computed values across different ray types.
Solution Approach 2:
The patent transforms the filtering operation from screen space to texture space, changing the dimensional domain of processing. This dimensionality change allows filters to operate on texture coordinates rather than pixel coordinates, enabling more efficient filtering that respects surface geometry and material properties while reducing computational overhead.
2Manufacturing precision
If more rays are traced per pixel, then image quality is improved, but rendering time increases
Solution Approach 1:
The patent performs preliminary tracing of guide rays to generate guide images before tracing primary rays. These guide images are used to guide the primary ray tracing process, enabling more efficient sampling strategies that reduce the total number of rays needed while maintaining image quality. The preliminary guide image computation informs subsequent primary ray generation.
Solution Approach 2:
The patent changes the sampling parameters dynamically based on local image properties derived from guide images. By adjusting ray density and filtering parameters according to scene complexity and material properties, the system achieves high image quality in important regions while using fewer rays in less critical areas, reducing overall rendering time.
3Manufacturing precision
If image-space filters are used for denoising, then noise removal is improved, but handling of camera effects and visibility discontinuities becomes difficult
Solution Approach 1:
The patent moves the filtering operation from screen space to texture space, changing the dimensional domain. This allows the filter to operate on texture coordinates where surface continuity is preserved, making it easier to handle camera effects like defocus and motion blur. The texture space formulation naturally handles visibility discontinuities by filtering along surface parameters rather than screen coordinates.
Solution Approach 2:
The patent applies different filtering strategies in different regions of the image based on local properties. By analyzing guide images to identify regions with camera effects or discontinuities, the system applies appropriate filtering parameters locally, maintaining noise removal quality while properly handling special cases that would be difficult with uniform filtering.
4Manufacturing precision
If existing denoising filters are implemented, then noise removal is improved, but memory footprint and computational overhead increase
Solution Approach 1:
The patent reformulates the filtering operation in texture space rather than screen space. This dimensional change allows the filter to operate on compact texture coordinate data rather than requiring large screen-space buffer structures. The texture space approach reduces memory footprint by eliminating the need for multiple full-screen auxiliary buffers while maintaining filtering effectiveness.
Data Source
AI summary
An apparatus and method are described for texture space shading. For example, one embodiment of a method comprises: performing texture mapping to map one or more textures to surfaces of one or more objects in texture space within a ray tracing architecture; and performing sampling and reconstruction directly on the surfaces of the objects in the texture space.