Perceptual Algorithms for HMD Display Power Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Head-mounted displays (HMDs) face challenges in reducing power consumption while maintaining high visual fidelity, as existing techniques often compromise image quality or are not suitable for all display types.
Innovation Solution
The use of machine learning models and design tools for unified display content perceptual and power analysis, allowing for the generation of images that save power while maintaining good visual fidelity, by applying techniques such as uniform dimming, luminance clipping, and brightness rolloff.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If display brightness is increased to improve visual fidelity, then image quality is improved, but power consumption increases
Solution Approach 1:
The patent applies local dimming techniques where different regions of the display are dimmed to different extents based on local image content analysis. Bright regions that contribute less to perceived image quality are dimmed more aggressively, while dark regions containing important visual information are preserved, achieving power savings without compromising overall visual fidelity.
Solution Approach 2:
The patent applies brightness reduction techniques selectively to portions of the display rather than uniformly across the entire display. By identifying and dimming only the portions of the image that are less critical to visual perception, the system achieves power savings while maintaining acceptable visual quality in the most important regions.
2Use of energy by moving object
If display content is modified to reduce power consumption, then energy efficiency is improved, but visual fidelity deteriorates
Solution Approach 1:
The patent employs feedback mechanisms where the system continuously monitors both power consumption metrics and visual quality metrics. Based on this feedback, the system dynamically adjusts dimming parameters to maintain visual fidelity within acceptable thresholds while maximizing power savings. The feedback loop enables real-time optimization of the trade-off between power consumption and image quality.
Solution Approach 2:
The patent dynamically changes display parameters such as brightness levels, contrast ratios, and color saturation in response to detected visual quality metrics. By adjusting these parameters based on real-time analysis of both power consumption and perceived image quality, the system maintains visual fidelity while achieving power savings.
3Use of energy by moving object
If existing power reduction techniques are applied, then power consumption is reduced, but they compromise image quality or are not suitable for all display types
Solution Approach 1:
The patent develops a universal power management system that can adapt to multiple display types including OLED, LCD, and micro-LED displays. The system incorporates display-type detection and automatically selects optimized processing algorithms for each display technology, enabling effective power reduction across diverse display platforms without compromising image quality or requiring separate solutions for each display type.
Data Source
AI summary
Techniques disclosed herein relate generally to modifying images to reduce display power while maintaining visual fidelity of the displayed images. In one example, a computer-implemented method includes receiving an input image to be displayed by a type of display device, obtaining a machine learning model that is trained to edit display content to reduce power consumption of displaying the edited display content by the type of display device while maintaining a visual fidelity of the edited display content, applying the machine learning model to the input image to generate an output image, and displaying the output image via a display device of the type of display device.