Content Adaptive Display Power Savings via AI Distortion Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern display devices, such as LCD and LED devices, face significant power consumption challenges due to backlights, which account for 20-25% of total power usage, and existing power-saving technologies often compromise image quality by uniformly reducing pixel brightness, leading to distortion.
Innovation Solution
A content adaptive display power management system that uses AI circuitry to adjust pixel intensity and backlight brightness individually, maintaining image quality by selecting distortion class pairs based on subjective image quality metrics like VMAF, allowing for variable power savings while minimizing distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If backlight brightness is reduced to save power, then power consumption decreases, but image quality deteriorates due to pixel distortion
Solution Approach 1:
The patent divides the display image into multiple regions with different luminance characteristics and applies different distortion compensation strategies to each region. This allows selective power savings in dark regions while maintaining image quality in bright regions, resolving the contradiction between power consumption and image quality.
Solution Approach 2:
The patent applies local quality by adjusting pixel values differently across various regions of the display based on local luminance requirements. Instead of uniform brightness reduction, each region receives customized processing to maintain optimal image quality while achieving power savings, directly addressing the contradiction.
2Use of energy by moving object
If uniform pixel brightness reduction is applied for power saving, then power consumption decreases, but image distortion increases
Solution Approach 1:
The patent implements dynamic adjustment of pixel values based on real-time analysis of image content and luminance distribution. The system continuously adapts the brightness reduction strategy to maintain image fidelity while achieving power savings, resolving the contradiction between power consumption and image stability.
Solution Approach 2:
The patent changes multiple parameters including pixel luminance values, regional weighting factors, and distortion compensation levels to achieve power savings without compromising image fidelity. This multi-parameter approach allows flexible optimization of both power consumption and image stability.
Data Source
AI summary
The present disclosure is directed to systems and methods for reducing display image power consumption while maintaining a consistent, objectively measurable, level of image distortion that comports with a display image quality metric. Raw image data is converted to an HSV format. “V” values are extracted from the HSV format raw image data and a histogram generates a plurality of “V” values. HSV format raw image data is provided to at least one layer of a trained CNN to extract a plurality of features. The plurality of “V” values and the plurality of features are provided to an AI circuit to generate a plurality of distortion class value pairs. Each of the distortion class value pairs is weighted based on proximity of display image distortion and the display image quality metric. The distortion class pair providing a display image distortion close to the display image quality metric is applied to the raw image data to generate the display image data.