AI-Generated Gamma Lookup Tables for Display Devices
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Solution Overview
Problem
Existing display devices face challenges in reducing power consumption while maintaining optimal grayscale representation, especially when switching between different driving frequencies.
Innovation Solution
A display device that utilizes a gamma lookup table generated through an artificial intelligence model, allowing for the generation of gamma voltages for a target driving frequency based on pre-existing gamma voltages for sample display devices driven at different frequencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If gamma voltages are manually adjusted for different driving frequencies, then grayscale representation can be optimized, but the process becomes complex and time-consuming
Solution Approach 1:
The patent creates a virtual model (AI model) that copies and generalizes the gamma voltage patterns from multiple sample display devices. This virtual model can generate appropriate gamma voltages for target display devices without requiring manual measurement and adjustment for each device, thus reducing complexity while maintaining grayscale accuracy.
Solution Approach 2:
The patent changes the approach from direct manual parameter adjustment to using an AI model that learns parameter relationships from training data. The model takes input parameters (such as display device characteristics) and automatically outputs the appropriate gamma voltage parameters, transforming a complex manual process into an automated parameter transformation task.
2Reliability
If gamma voltages are optimized for each display device, then image quality improves, but the time and resources required increase significantly
Solution Approach 1:
The patent performs preliminary actions by training the AI model on a diverse set of sample display devices before deployment. This pre-training process captures the essential relationships between display characteristics and optimal gamma voltages, enabling rapid generation of appropriate gamma voltages for new display devices without requiring time-consuming manual optimization for each device.
Solution Approach 2:
The AI model enables display devices to self-determine their optimal gamma voltages based on their own characteristics and the learned patterns from training data. This self-service capability eliminates the need for external manual optimization processes, significantly reducing the time and resources required while maintaining image quality.
3Use of energy by moving object
If multiple gamma lookup tables are stored for different driving frequencies, then power consumption can be reduced, but memory requirements and system complexity increase
Solution Approach 1:
The patent introduces dynamics by replacing static, pre-stored gamma lookup tables with a dynamic AI model that can adaptively generate appropriate gamma voltages based on the current driving frequency and display device characteristics. This dynamic approach allows the system to maintain power efficiency across multiple frequencies without requiring separate lookup tables for each frequency, thereby reducing memory requirements and system complexity.
Data Source
AI summary
A display device includes a display panel including a sub-pixel, a data driver configured to generate a data voltage based on a gamma voltage and provide the data voltage to the sub-pixel, and a gamma voltage generator configured to receive a first gamma lookup table and a second gamma lookup table and generate the gamma voltage based on at least one of the first gamma lookup table and the second gamma lookup table, and provide the gamma voltage to the data driver. The display device trains an artificial intelligence model to generate the second gamma lookup table comprising gamma voltages for a target driving frequency using the first gamma lookup table including gamma voltages for a sample display device driven at different respective sample driving frequencies.