Flexible Scale Rasterization for Focal-Area Image Rendering
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Solution Overview
Problem
Existing image processing systems require significant processing power to generate high-quality immersive content, particularly for virtual reality, due to the need for high-resolution rendering across the entire image, which can be inefficient and resource-intensive.
Innovation Solution
Implementing flexible scale rasterization (FSR) to vary the rasterization rate based on the position within the image, using metadata to manage texture warping and shader modifications efficiently, allowing for reduced processing requirements while maintaining image quality in focal areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-resolution rendering is applied across the entire image, then image quality is improved, but processing power requirements increase
Solution Approach 1:
The patent applies different rendering qualities to different regions of the image based on their importance. High-resolution rendering is applied only to focal areas that require high quality, while non-focal areas use lower resolution. This resolves the contradiction by maintaining high image quality where needed while reducing overall processing power requirements.
Solution Approach 2:
The patent segments the image into multiple regions with different quality requirements - focal areas and non-focal areas. By dividing the rendering process into separate quality levels for different segments, the system achieves high quality output without requiring high processing power across the entire image.
2Power
If foveal rendering with eye gaze tracking is implemented, then processing power is reduced, but system complexity increases
Solution Approach 1:
The patent provides a universal rendering framework that can operate with or without eye tracking. The system accepts gaze position input when available (reducing processing power) but can function without it by using alternative focal area determination methods, thus reducing system complexity while maintaining processing efficiency.
Solution Approach 2:
The patent introduces an intermediary mechanism that determines focal areas through multiple methods including eye gaze tracking, content-based cues, and prediction algorithms. This intermediary layer manages the complexity by providing a unified interface that selects the appropriate method based on system capabilities, reducing the burden on the overall system.
3Power
If resolution is reduced in non-focal areas, then processing power is reduced, but image quality deteriorates
Solution Approach 1:
The patent applies local quality enhancement by rendering high-resolution content specifically for focal areas while using lower resolution for non-focal areas. This ensures that processing power is reduced overall while image quality is maintained in the regions that matter most to the user experience.
Data Source
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AI summary
An image processing system operable to generate one or more images for display, the system comprising a rendering unit operable to render one or more of a plurality of textures using flexible scale rasterization, FSR, a metadata generation unit operable to generate metadata indicating one or more properties of the FSR used to render a corresponding texture, a shader compiler operable to read the metadata, and to modify a shader to enable a texture sampling to be performed that includes an FSR resolve where the metadata indicates that a corresponding texture has been rendered with FSR, and an image generation unit operable to generate an image for display using at least one modified shader, the generated image including one or more of the plurality of textures.