VR Image Quality via Frequency-Based Resolution Segmentation
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Solution Overview
Problem
Current anti-aliasing techniques in computer graphics lack adequate pixel accuracy and temporal stability, causing perceptible blurring and inefficiencies in rendering quality, especially in real-time graphics and virtual reality applications.
Innovation Solution
A method and device that divide image data into areas corresponding to different resolutions based on sensing information and frequencies, allowing for rendering in a single pass and dynamic adjustment of rendering quality, using a graphics processing unit and memory to improve image quality by dynamically adjusting rendering frequencies and workload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If supersampling is used to render the entire scene at a higher resolution, then image quality is improved, but performance cost and memory bandwidth usage increase significantly
Solution Approach 1:
The patent applies different rendering resolutions to different spatial regions of the image based on their frequency content. High-frequency regions (edges, details) are rendered at higher resolution while low-frequency regions (smooth areas) are rendered at lower resolution, achieving overall image quality improvement without uniformly high performance cost
Solution Approach 2:
The image is divided into multiple regions or zones with different frequency characteristics, and each region is rendered at an appropriate resolution level. This segmentation allows selective application of high-resolution rendering only where necessary, reducing overall performance cost while maintaining image quality
2Object-generated harmful factors
If existing anti-aliasing techniques are applied, then aliasing is reduced, but pixel accuracy and temporal stability are insufficient causing perceptible blurring
Solution Approach 1:
The patent dynamically adjusts rendering parameters such as resolution and sampling rate based on the frequency content of different image regions. By changing these parameters adaptively rather than using fixed anti-aliasing settings, the system achieves better pixel accuracy while maintaining temporal stability across frames
3Manufacturing precision
If the entire graphics pixel pipeline is adjusted to optimize quality, then image quality improves, but rendering efficiency decreases due to increased complexity
Solution Approach 1:
Instead of adjusting the entire graphics pipeline uniformly, the patent applies quality optimizations only to specific regions that require them based on frequency analysis. This localized approach maintains rendering efficiency in regions where high quality is not critical
Solution Approach 2:
The graphics rendering process is segmented into different passes or stages, with frequency-based region identification occurring early to guide subsequent rendering decisions. This segmentation allows efficient processing by avoiding unnecessary complexity in regions where simple rendering suffices
Data Source
AI summary
A method for improving image quality is provided. The method includes: receiving an image data and sensing information; dividing the image data into areas corresponding to different resolutions according to first parameter information, wherein the different resolutions correspond to different frequencies; rendering the areas in a single pass according to the sensing information and the different frequencies and outputting a rendered image data; and resolving the rendered image data into a final output image data with a first resolution according to second parameter information.