Bilinear Approximation for Image Rendering Sample Test Efficiency
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Solution Overview
Problem
Conventional image rendering techniques face inefficiencies in sample test efficiency, particularly with motion blur and defocus blur, leading to low sample test efficiency and image quality issues when handling fast motion and complex geometric transformations.
Innovation Solution
A method is introduced that constructs a bilinear approximation for a screen space region to estimate the coverage of primitives, reducing the number of samples tested by excluding non-covered sample points and using combined time and lens bounds to maintain high sample test efficiency even with combined motion and defocus blur.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time-continuous triangles are used to handle motion blur, then image quality is improved, but sample test efficiency degrades drastically
Solution Approach 1:
The patent segments the time interval into discrete time steps and processes samples in batches at each time step. This allows the system to maintain high sample test efficiency by processing only relevant samples at each discrete time step rather than continuously, while still achieving the image quality of time-continuous triangles through accumulated results across all time steps.
Solution Approach 2:
The patent performs preliminary actions by pre-calculating time bounds and lens bounds for each sample point before the main rendering loop. This preliminary computation of coverage bounds allows the system to quickly determine which samples need to be tested at each time step, significantly improving sample test efficiency while maintaining image quality.
2Ease of manufacture
If a fixed set of unique time values is used for rendering, then implementation is simple, but the solution does not scale to a large number of samples per pixel
Solution Approach 1:
The patent transitions from a static fixed set of time values to a dynamic approach where time bounds are calculated for each sample point based on the specific rendering conditions. This dynamic calculation of time intervals allows the system to adapt to varying numbers of samples per pixel while maintaining implementation simplicity through a systematic batch-processing approach.
3Measurement precision
If all sample points are tested to ensure accuracy, then image quality is maintained, but rendering time increases significantly
Solution Approach 1:
The patent performs preliminary computation of time bounds and lens bounds for each sample point before the main rendering loop. This preliminary action determines which samples are potentially covered by the primitive at each time step, allowing the system to test only relevant samples and significantly reduce rendering time while maintaining image quality through accurate bound calculation.
Solution Approach 2:
The patent extracts and removes samples that are definitely not covered by the primitive based on pre-calculated bounds. By taking out these obviously non-covered samples from the testing pool, the system reduces the number of samples that need to be tested, thereby reducing rendering time while maintaining image quality for the samples that are actually covered.
Data Source
AI summary
A method for reducing the number of samples tested for rendering a screen space region of an image includes constructing a bilinear approximation per primitive for a screen space region which is to be rendered, wherein the screen space region includes a plurality of sample points. The bilinear approximation is used to estimate coverage of a predefined primitive against one or more sample points within the screen space region. At least one sample point in the screen space region which is not covered by the predefined primitive is excluded from testing in the rendering of the screen space region.