Mura Correction Driver Adaptive Range Coefficients
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Solution Overview
Problem
Display panels suffer from Mura defects, which result in non-uniform luminance and require effective detection and correction to improve image quality, but existing methods struggle to accurately correct brightness values beyond the representation range of basic coefficients and are prone to errors.
Innovation Solution
A Mura correction driver utilizing a quadratic Mura correction equation with adaptive range capabilities, applying coefficient values to adjust brightness representation ranges and incorporating display brightness value control to eliminate errors, thereby correcting Mura blocks and pixels effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a basic range bit coefficient is used in the Mura correction equation, then the device complexity is reduced, but the brightness value correction range is limited and cannot correct Mura defects beyond the basic representation range
Solution Approach 1:
The coefficient is segmented into multiple parts: an integer part and a fractional part, each stored in separate memory locations. This segmentation allows the system to represent coefficients beyond the basic range while maintaining manageable complexity through modular storage and processing
Solution Approach 2:
The patent extends the coefficient representation from a single-dimensional basic range to a multi-dimensional structure by combining integer and fractional parts with different bit allocations. This dimensional extension enables correction of brightness values beyond the original representation range
2Manufacturing precision
If the coefficient representation range is extended to correct brighter Mura blocks, then the brightness value correction capability is improved, but the number of bits required increases and may exceed basic range limits
Solution Approach 1:
Different portions of the coefficient (integer part vs. fractional part) are allocated different bit widths based on their specific requirements. The integer part uses more bits to represent the magnitude, while the fractional part uses fewer bits, optimizing the overall bit usage for the specific correction needs
Solution Approach 2:
The patent changes the parameter representation by separating the coefficient into integer and fractional components with different precision requirements. This parameter transformation allows efficient use of bit resources while achieving the required correction precision across different brightness ranges
3Measurement precision
If a quadratic Mura correction equation is applied, then the Mura correction accuracy is improved, but errors may occur in the correction process that need to be eliminated
Solution Approach 1:
The patent incorporates feedback mechanisms where the correction process monitors its own output and adjusts subsequent corrections accordingly. This feedback loop helps identify and eliminate errors that occur during quadratic correction, improving overall reliability while maintaining high accuracy
Solution Approach 2:
The system prepares compensation values in advance that cushion against potential errors in the quadratic correction process. By pre-calculating adjustment values based on expected error patterns, the system can counteract errors before they manifest in the final display output
Data Source
AI summary
A Mura correction driver which corrects Mura detected in a detection image obtained by photographing a display panel. The Mura correction driver uses Mura correction data including a position value of a Mura block for a display panel and coefficient values for the Mura block, and corrects display data corresponding to the position value of the Mura block, by using a Mura correction equation to which the coefficient values of the Mura block are applied.