OLED Image Control System Using Histogram Analysis
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Solution Overview
Problem
Existing methods for controlling OLED panels fail to effectively process image data, leading to inadequate image quality and increased power consumption, as they rely on average luminance calculations that do not fully represent image content, and require significant computational resources.
Innovation Solution
A method and system that utilize histogram distribution analysis to determine image features, allowing for parameter control and adjustment, including luminance enhancement, contrast adjustment, and pixel degradation protection, to optimize image quality and reduce power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If average luminance calculation is used to determine image content, then the processing is simple, but the image quality is insufficient because average value cannot represent entire image content
Solution Approach 1:
The image frame is divided into multiple blocks, and each block is further divided into sub-blocks for histogram analysis. This segmentation allows the system to capture local image features while maintaining manageable processing complexity through systematic organization of the analysis structure.
Solution Approach 2:
The patent transitions from analyzing a single average luminance value to generating two-dimensional histogram distributions that show the frequency distribution of luminance values across different blocks. This dimensional expansion provides comprehensive image content representation while using efficient bit manipulation techniques to manage the increased data complexity.
2Measurement precision
If image frame is divided into multiple blocks for analysis, then image content representation improves, but computational resources and circuit area increase
Solution Approach 1:
The patent replaces complex computational operations with bit manipulation techniques. By using bit shifts and bitwise operations to calculate histogram distributions and determine image features, the system achieves accurate image analysis with significantly reduced computational overhead and circuit complexity compared to traditional floating-point arithmetic methods.
3Use of energy by moving object
If traditional image processing is used, then power consumption is high, but image quality is insufficient
Solution Approach 1:
The patent substitutes energy-intensive traditional image processing algorithms with efficient bit manipulation operations. The histogram-based analysis using bitwise operations requires significantly less power while providing superior image content representation, thereby resolving the contradiction between power consumption and image quality.
Solution Approach 2:
The patent changes the processing parameters from continuous luminance values to discrete histogram bins, and from average value calculations to distribution-based analysis. This parameter transformation enables more accurate image characterization while reducing the computational power required for processing.
Data Source
AI summary
A method of controlling image data includes the steps of: receiving an image frame; generating an image data distribution of the image frame; and controlling a parameter for displaying the image frame according to the image data distribution.