Selective Pixel Antialiasing for Complex Geometry Rendering
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Solution Overview
Problem
Current antialiasing methods incur high storage costs and bandwidth usage, and are complicated for complex geometry rendering, often requiring multiple rendering passes.
Innovation Solution
Identify complex pixels using conservative rasterization, perform ray tracing on these pixels to determine higher sampling rates, and adjust sampling costs per pixel, utilizing a parallel processing unit (PPU) for efficient antialiasing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If current antialiasing methods are applied to remove image artifacts, then image realism is improved, but storage costs and bandwidth usage increase significantly
Solution Approach 1:
The patent applies antialiasing selectively only to complex pixels that are partially covered by geometry, rather than uniformly to all pixels. This local quality approach maintains image realism where needed while reducing storage costs and bandwidth usage for fully covered pixels that do not require antialiasing processing.
Solution Approach 2:
The patent segments the image processing into two distinct categories: complex pixels requiring antialiasing and non-complex pixels that do not. By identifying and separating these pixel types through conservative rasterization, the system applies different processing strategies to each segment, optimizing both image quality and resource utilization.
2Manufacturing precision
If current antialiasing methods are applied to remove image artifacts, then image realism is improved, but bandwidth usage increases significantly
Solution Approach 1:
The patent applies antialiasing selectively only to complex pixels that are partially covered by geometry, rather than uniformly to all pixels. This local quality approach maintains image realism where needed while reducing storage costs and bandwidth usage for fully covered pixels that do not require antialiasing processing.
Solution Approach 2:
The patent performs antialiasing on a partial set of pixels (only complex pixels) rather than all pixels in the image. This partial action approach achieves sufficient image realism by targeting only the pixels that exhibit aliasing artifacts, thereby reducing bandwidth usage compared to full-image antialiasing.
3Manufacturing precision
If several rendering passes are performed over a scene for antialiased deferred rendering, then complex geometry rendering quality is improved, but device complexity and processing time increase
Solution Approach 1:
The patent performs conservative rasterization in advance to identify complex pixels before the main rendering pass. This preliminary action allows the system to prepare a mask of pixels requiring antialiasing, enabling single-pass deferred rendering with improved quality without requiring multiple rendering passes.
Solution Approach 2:
The patent segments the image processing into two distinct categories: complex pixels requiring antialiasing and non-complex pixels that do not. By identifying and separating these pixel types through conservative rasterization, the system applies different processing strategies to each segment, optimizing both image quality and resource utilization.
4Ease of operation
If uniform sampling is applied to all pixels, then processing simplicity is maintained, but processing efficiency decreases due to unnecessary sampling of fully covered pixels
Solution Approach 1:
The patent applies antialiasing selectively only to complex pixels that are partially covered by geometry, rather than uniformly to all pixels. This local quality approach maintains image realism where needed while reducing storage costs and bandwidth usage for fully covered pixels that do not require antialiasing processing.
Solution Approach 2:
The patent performs antialiasing on a partial set of pixels (only complex pixels) rather than all pixels in the image. This partial action approach achieves sufficient image realism by targeting only the pixels that exhibit aliasing artifacts, thereby reducing bandwidth usage compared to full-image antialiasing.
Data Source
AI summary
During the rendering of an image, specific pixels in the image are identified where antialiasing would be helpful. Antialiasing is then performed on these identified pixels, where antialiasing is a technique used to add greater realism to a digital image by smoothing jagged edges. This reduces a cost of performing antialiasing by reducing a number of pixels within an image on which antialiasing is performed.