Multi-sample Resolving for 3D Image Depth Tearing Reduction
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Solution Overview
Problem
Existing three-dimensional re-projection methods suffer from depth tearing artifacts due to fixed sample locations within pixels, leading to discrete shifts in perceived depth planes rather than smooth transitions, which is exacerbated by hardware memory constraints and increased memory requirements for higher resolutions.
Innovation Solution
The method involves determining the coverage amounts of multiple samples associated with each three-dimensional pixel, using 'leading' and 'trailing' samples, and weighting their contributions to calculate final pixel values, allowing for more accurate and smooth color transitions during re-projection, thereby reducing depth tearing and improving visual quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed sample locations within pixels are used for three-dimensional re-projection, then hardware memory constraints are managed, but depth tearing artifacts occur and smooth transitions in perceived depth planes are lost
Solution Approach 1:
The patent applies dynamics by making sample locations movable rather than fixed. The sample locations are shifted based on depth values to achieve smooth transitions in perceived depth planes. This dynamic adjustment of sample positions during re-projection eliminates depth tearing artifacts while managing hardware memory constraints through efficient sample sharing.
2Manufacturing precision
If multiple samples per pixel are used to reduce aliasing artifacts, then spatial continuity is improved, but memory requirements increase
Solution Approach 1:
The patent merges sample data from multiple pixels by allowing samples to be shared across different pixels based on depth-based positioning. Instead of allocating dedicated multiple samples per pixel which would increase memory requirements, the system combines sample usage across pixels dynamically, achieving spatial continuity improvement without proportional memory increase.
Solution Approach 2:
The patent changes the parameter of sample positioning from fixed to dynamic based on depth values. By adjusting sample locations according to depth information, the system achieves better spatial continuity and reduces aliasing artifacts while maintaining efficient memory utilization through adaptive sample allocation.
3Manufacturing precision
If higher resolution is used to eliminate aliasing artifacts, then visual quality improves, but memory constraints are exceeded
Solution Approach 1:
The patent uses copying by allowing the same sample data to be copied and used by multiple pixels based on depth-based positioning. Instead of storing separate high-resolution data for each pixel which would exceed memory constraints, the system copies sample data to appropriate pixel locations dynamically, achieving high visual quality within memory limits.
Data Source
AI summary
Multi-sample resolution of a re-projection of a two-dimensional image is disclosed. One or more samples of a two-dimensional image are identified for each pixel in the three-dimensional re-projection. One or more sample coverage amounts are determined for each pixel of the re-projection. Each coverage amount identifies an area of the pixel covered by the corresponding two-dimensional sample. A final value is resolved for each pixel of the re-projection by combining each two-dimensional sample associated with the pixel in accordance with its weighted sample coverage amount.