Texture Coordinate Randomization for Moiré Artifact Reduction
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Solution Overview
Problem
Existing methods for reducing image artifacts such as Moiré patterns in high-resolution images with densely patterned textures often result in a loss of image data and decreased quality due to post-processing adjustments.
Innovation Solution
The approach involves randomizing texture coordinates for pixels or sample locations in each frame before sampling, while constraining the randomization to ensure that sample positions remain within pixel bounds, thereby avoiding blurring and other artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If post-processing adjustments are applied to reduce image artifacts, then artifact reduction is improved, but image quality deteriorates due to loss of image data
Solution Approach 1:
The patent applies preliminary action by randomizing texture coordinates before the sampling process occurs. This pre-randomization prevents Moiré pattern formation at the source rather than attempting to correct it afterward. By constraining random offsets to sub-pixel ranges and applying them before texture sampling, the system eliminates artifacts during the rendering process itself, avoiding the need for post-processing that would degrade image quality.
2Object-affected harmful factors
If texture coordinates are randomized to avoid Moiré patterns, then artifact reduction is improved, but blurring may occur if constraints are not applied
Solution Approach 1:
The patent applies local quality by implementing different levels of randomization constraints for different spatial locations. The random offset is constrained to be less than a threshold value (sub-pixel range) rather than fully randomizing across the entire pixel area. This localized constraint approach prevents Moiré patterns while preserving the sharpness and detail of the original texture, as the randomization is limited to the sub-pixel region where it can effectively disrupt patterns without causing overall blurring.
Data Source
AI summary
Approaches presented herein provide for removal or reduction of anti-aliasing artifacts, such as Moiré patterns or staircasing, in an image to be rendered. In many instances, these artifacts correspond to regular texture patterns with fine detail, and the addition of randomization in sampling position can help to remove the impact of the regularity of the pattern. In at least one embodiment, a first order approximation can be used that introduces a random amount of shifting determined using texture coordinate derivatives. The random amount can account for any jitter offset, and shift the texture coordinates by the determined random amount, such that sample selected for that pixel will select from a sample location that corresponds to the random shift but is constrained to be within the bounds of the pixel.