Defect Pixel Determination Using Edge Periphery Difference Calculation
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Solution Overview
Problem
Existing defect pixel correction technologies, such as static and dynamic type defect correction methods, face challenges in accurately identifying defect pixels near edges with similar pixel values, leading to incomplete defect correction due to limited determining conditions.
Innovation Solution
The proposed solution involves an apparatus with first and second difference calculating units to determine defect pixels by calculating differences between maximum and minimum pixel values within specific pixel groups adjacent to the central pixel, and a determination unit that assesses these differences and pixel values to accurately identify defect pixels, even when neighboring edges have similar values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a simple difference value calculation method is used between average pixel values of neighboring pixels and the corresponding pixel, then the calculation process is simple, but defect pixels neighboring to edges with similar values cannot be determined as defects
Solution Approach 1:
The patent segments the pixel group into multiple sub-groups (first pixel group and second pixel group) with different characteristics. Each sub-group is evaluated separately using different difference calculation methods, allowing the system to handle edge cases with similar values while maintaining overall system simplicity.
Solution Approach 2:
The patent applies different difference calculation approaches to different local regions (sub-groups) of the pixel group. For regions where simple average difference works, it uses that method; for edge regions with similar values, it uses maximum/minimum based difference calculation, optimizing accuracy locally without complicating the entire system.
2Device complexity
If a defect determining condition is limited to cases where the pixel value is the maximum value in the setting window, then the determination condition is simple, but defect pixels neighboring to edges with similar values cannot fully be determined as defects
Solution Approach 1:
The patent divides the pixel group into multiple sub-groups and applies different determination conditions to each sub-group. This segmentation allows the system to use simple maximum value conditions for most cases while applying more robust maximum/minimum difference conditions for edge cases, improving overall reliability without excessive complexity.
Solution Approach 2:
The patent changes the determination parameters dynamically based on the sub-group characteristics. For different sub-groups, it uses different parameter combinations (average difference, maximum difference, minimum difference), allowing reliable defect detection across various pixel value distributions while keeping individual determination conditions simple.
3Object-affected harmful factors
If settings are made to reduce adverse effects in existing methods, then the adverse effect is reduced, but defect pixels neighboring to edges with similar values still cannot fully be determined as defects
Solution Approach 1:
By segmenting the pixel group into sub-groups with different characteristics, the patent can apply targeted difference calculation methods to each segment. This ensures that edge cases with similar values are handled with appropriate maximum/minimum based calculations, achieving both adverse effect reduction and high determination accuracy.
Solution Approach 2:
The patent applies local quality optimization by using different difference calculation strategies for different sub-groups. Regions prone to adverse effects from similar values receive specialized handling through maximum/minimum difference calculation, while other regions use simpler methods, achieving both goals simultaneously.
Data Source
AI summary
Provided is an apparatus of determining a defect pixel which includes at least one of a first edge periphery defect determiner and a second edge periphery defect determiner, wherein the first edge periphery defect determiner is configured to determine if a central pixel of a pixel group is the defect pixel by using pixel values of pixels adjacent to the central pixel disposed close to an image edge, wherein the edge includes at least one of right, left, upper, lower, lower-left, lower-right, upper-left and upper-right pixels of the central pixel, and wherein the second edge periphery defect determiner is configured to determine if the central pixel is the defect pixel by using a pixel disposed at at least one of the lower-left, lower-right, upper-left and upper-right of the central pixel.