Temporal Filter Weighting for Low-Light Mixed-Reality Imaging
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Solution Overview
Problem
Existing temporal filtering methods in mixed-reality systems face challenges in selecting appropriate weights for combining image frames, leading to issues such as image artifacts, reduced frame rate, and increased latency, particularly in low-light and motion-intensive environments.
Innovation Solution
Regulating filter strength based on signal level-dependent and motion compensation reliability-dependent factors, using a weight function that adjusts weights according to light level and motion compensation confidence, to balance image quality and artifact reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If temporal filtering is applied to improve image quality in low-light conditions, then image quality is improved, but image artifacts and reduced frame rate occur
Solution Approach 1:
The patent applies dynamic filter strength adjustment based on motion compensation confidence. The filter strength is not fixed but varies dynamically according to the reliability of motion compensation and lighting conditions. When motion compensation confidence is high and lighting is poor, stronger filtering is applied; when confidence is low or lighting is good, filtering is reduced or disabled, thus adapting the frame rate impact to actual needs.
Solution Approach 2:
The patent changes the parameter of filter strength based on multiple conditions including light level indicators and motion compensation confidence indicators. By adjusting this parameter dynamically according to environmental conditions and motion characteristics, the system optimizes the balance between image quality improvement and frame rate maintenance.
2Reliability
If temporal filtering with motion compensation is used to reduce image artifacts, then image quality is improved, but processing complexity and latency increase
Solution Approach 1:
The patent applies temporal filtering selectively rather than universally. By using motion compensation confidence indicators to determine when filtering is actually needed, the system avoids unnecessary processing in cases where motion compensation is unreliable or lighting conditions don't benefit from filtering, thus reducing overall processing complexity while maintaining image quality where it matters.
Solution Approach 2:
The patent implements a feedback mechanism where motion compensation confidence indicators and light level indicators are continuously monitored to adjust filter strength. This feedback loop allows the system to adapt processing complexity to actual performance needs, reducing latency by avoiding unnecessary filtering operations when confidence is low.
3Illumination intensity
If high filter strength is applied to combine multiple frames, then image quality in low-light is improved, but motion artifacts and ghosting increase
Solution Approach 1:
The patent dynamically adjusts filter strength based on motion compensation confidence indicators. When confidence is high, stronger filtering can be applied to improve low-light images; when confidence is low (indicating significant motion), filtering is reduced to prevent motion artifacts and ghosting effects.
Solution Approach 2:
The filter strength parameter is changed based on multiple inputs including light level indicators and motion compensation confidence indicators. This allows the system to optimize the balance between improving image brightness in low-light conditions and preventing motion-related artifacts by adapting the parameter to current scene characteristics.
Data Source
AI summary
A system for regulating temporal filtering strength is configurable to: (i) obtain a light level indicator indicating light level associated with a real-world environment; (ii) determine a motion compensation confidence indicator using a current image and a previous image; (iii) determine a filter weight by processing the light level indicator and the motion compensation confidence indicator using a filter strength regulation module; and (iv) generate an output image by using at least the filter weight to filter a current frame with a previous frame.