Direct-Lit Backlight Content-Type Brightness Control
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Solution Overview
Problem
Direct-lit backlights in electronic devices face challenges in achieving optimal dynamic range and power efficiency while minimizing visible artifacts such as clipping and halo effects, due to uniform brightness control of light-emitting diodes, which affects the aesthetic quality and power consumption.
Innovation Solution
Implementing a neural network-based system that analyzes image data to determine content type probabilities, allowing for dynamic adjustment of light-emitting diode brightness values based on content type, thereby optimizing backlight illumination across the display to mitigate artifacts and manage power consumption effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If uniform brightness control is used for all light-emitting diodes, then device complexity is reduced and ease of manufacture is improved, but dynamic range enhancement is limited and visible artifacts such as clipping and halo effects occur
Solution Approach 1:
The patent implements local brightness control by dividing the backlight into multiple independently controllable light-emitting diode regions. Each region's brightness is adjusted based on local content characteristics analyzed by a neural network, allowing different parts of the display to have different brightness levels. This resolves the contradiction by enabling high image quality through local optimization without requiring complex global control systems.
Solution Approach 2:
The patent employs dynamic brightness adjustment where the brightness of each light-emitting diode region is continuously adapted based on the displayed content type probability determined by a neural network. This dynamic control allows the system to optimize image quality for different content types (e.g., photos, videos, UI) while maintaining manageable device complexity through automated content analysis.
2Use of energy by moving object
If local dimming is implemented to enhance dynamic range, then power consumption is reduced and dynamic range is enhanced, but device complexity increases and visible artifacts may be produced
Solution Approach 1:
The patent implements a self-service mechanism where the neural network automatically analyzes display content and determines optimal brightness settings for each light-emitting diode region based on content type probability. This eliminates the need for complex manual control systems or additional sensors, as the system self-regulates power consumption and brightness distribution based on content requirements, reducing both power consumption and control complexity.
Solution Approach 2:
The system uses feedback from the neural network's content analysis to dynamically adjust brightness settings. The neural network continuously evaluates displayed content and provides feedback signals that control the brightness of individual LED regions, enabling efficient power management while maintaining simple control architecture through intelligent automated decision-making.
3Loss of energy
If local dimming is implemented to reduce power consumption, then energy efficiency is improved, but device complexity increases and visible artifacts such as halo effects occur
Solution Approach 1:
The patent applies preliminary action by using the neural network to predict content type probability before final brightness rendering. This pre-analysis allows the system to anticipate when local dimming should be applied and when uniform brightness is more appropriate, preventing the formation of visible artifacts by preparing optimal brightness settings in advance based on content characteristics.
Solution Approach 2:
The system dynamically changes brightness parameters based on content type probability determined by the neural network. By adjusting brightness levels according to content requirements (e.g., higher brightness for UI elements, lower for dark scenes), the system optimizes energy efficiency while maintaining image aesthetic quality through intelligent parameter adaptation rather than fixed dimming rules.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the dynamic range of the display, reduces visible artifacts, and optimizes power usage by varying brightness levels according to content type, providing an aesthetically pleasing and energy-efficient solution.
Implementation Method 1
a backlight unit having light-emitting diodes that are configured to produce backlight illumination for the pixel array
Data Source
AI summary
A display may have a pixel array such as a liquid crystal pixel array. The pixel array may be illuminated by a backlight unit that includes an array of light-emitting diodes (LEDs). The backlight unit may determine the type of content in the image data. The backlight unit may decide to prioritize either mitigating halo or mitigating clipping based on the type of content. The determination of the type of content in the image data may be used to determine the brightness values for the LEDs in the LED array. If the content is determined to be a first type of content, at least one given LED in the LED array may have a different brightness value than if the content is determined to be a second, different type of content. Classifying content in the image data may be useful in optimizing visible artifacts such as visible halo and clipping.