Adaptive Image Brightness Enhancement for VST XR Low-Light Frames
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Solution Overview
Problem
Extended reality (XR) systems, particularly video see-through (VST) XR devices, face challenges in maintaining image quality due to varying brightness levels in captured frames, leading to dark and noisy images, which affect user experience and comfort.
Innovation Solution
Dynamic and adaptive image brightness enhancement techniques that segment frames into regions, analyze regional and global brightness parameters, and apply localized and global enhancements to achieve consistent brightness across the entire frame.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If global brightness enhancement is applied to the entire image frame, then overall brightness is improved, but regions that already have sufficient brightness become overexposed and lose detail
Solution Approach 1:
The image frame is divided into multiple regions, and brightness enhancement is applied selectively to each region based on its specific brightness characteristics. This allows different brightness adjustments for different areas, preventing overexposure in already bright regions while enhancing dark regions.
Solution Approach 2:
Different brightness enhancement strategies are applied to different regions of the image frame based on local brightness conditions. Each region receives customized brightness adjustment rather than a uniform global adjustment, ensuring optimal brightness uniformity across the entire frame.
2Illumination intensity
If brightness enhancement is applied to dark regions, then visibility is improved, but noise in low-light regions increases
Solution Approach 1:
The brightness enhancement process dynamically adjusts enhancement parameters based on the specific brightness and noise characteristics of each region. By adapting the enhancement strength to local conditions, the system improves visibility in dark regions while minimizing noise amplification.
Solution Approach 2:
The system analyzes the brightness and noise levels of each region and uses this feedback to control the strength of brightness enhancement applied. This feedback mechanism ensures that enhancement is strong enough to improve visibility but not so strong as to excessively amplify noise.
3Manufacturing precision
If region-specific brightness enhancement is applied, then brightness uniformity is improved, but processing complexity increases
Solution Approach 1:
The image frame is divided into a limited number of regions, which balances the ability to apply region-specific enhancements with the computational complexity of processing. This segmentation approach enables brightness uniformity improvement without requiring excessive processing resources.
Data Source
AI summary
A method includes obtaining, using at least one imaging sensor of an electronic device, a color image frame of a scene. The method also includes determining, using at least one processing device of the electronic device, that a visual quality of the color image frame falls outside of a visual quality threshold. The method further includes, in response to determining that the visual quality of the color image frame falls outside of the visual quality threshold, performing, using the at least one processing device, visual quality enhancement to the color image frame to generate a modified image frame. In addition, the method includes applying, using the at least one processing device, one or more passthrough transformations to the modified image frame to generate a transformed image frame.