Adaptive Luminance Profile Data Thinning for Backlight Control
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Solution Overview
Problem
Existing image display devices using liquid crystal panels and backlight devices face challenges in reducing luminance profile data while maintaining precision, as simple thinning methods can delete critical data portions, affecting image contrast and power consumption.
Innovation Solution
An information processing method that adjusts thin-out spacing in luminance profile data based on spatial luminance variation to generate reduced data sets that preserve the features of the original data, allowing for precise luminance distribution calculations with lower data amounts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If simple thinning or reduction methods are applied to luminance profile data, then the data amount is reduced, but critical luminance distribution features are deleted
Solution Approach 1:
The patent applies local quality by dividing the luminance profile data into multiple regions based on spatial luminance variation characteristics. Different thinning strategies are applied to different regions: regions with high luminance variation retain more data points, while regions with low variation undergo more aggressive thinning. This region-specific approach preserves critical luminance distribution features while reducing overall data amount.
Solution Approach 2:
The patent implements dynamic thinning by adjusting the thinning ratio based on the local luminance variation characteristics of each region. The thinning process is not static but adapts to the actual data characteristics, using metrics such as standard deviation or gradient magnitude to determine the appropriate thinning intensity for each region, thereby optimizing the balance between data reduction and feature preservation.
2Measurement precision
If high precision luminance distribution calculation is maintained, then image contrast is improved, but power consumption increases
Solution Approach 1:
The patent extracts only the essential luminance profile data points needed for accurate luminance distribution calculation by removing redundant data points through the adaptive thinning process. By selectively retaining critical data points that capture luminance variation characteristics while discarding redundant information, the system achieves precise calculations with reduced computational load and lower power consumption.
Solution Approach 2:
The patent changes the parameter of data quantity by transforming the original dense luminance profile data into a sparser representation through adaptive thinning. This parameter transformation maintains the essential luminance distribution characteristics while reducing the computational resources required for processing, thereby lowering power consumption without sacrificing calculation precision.
Data Source
AI summary
An information processing method, including: generating second luminance profile data by inputting first luminance profile data of a spreading of light when one light source of a backlight device including at least one light source is lit, and adjusting a thin-out spacing according to positions in a luminance distribution based on the first luminance profile data. Values of the first luminance profile data are thinned in the second luminance profile data.