Pixel Defect Compensation Using Luminance Level Comparison
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Solution Overview
Problem
Existing imaging apparatuses struggle to accurately compensate for pixel signals from defective pixels in solid-state imaging devices, especially when neighboring pixels are also defective, leading to erroneous compensation and poor image quality.
Innovation Solution
The apparatus employs an optical filter with color filters arranged in horizontal and vertical directions, generating pixel signals from target and neighboring pixels, and uses a combination of highest and second-highest luminance levels to determine pixel defectiveness, replacing defective pixel signals with those from neighboring pixels to prevent erroneous compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a pixel signal from a defective pixel is compensated by being replaced with a pixel signal of a neighboring pixel, then the defective pixel can be compensated, but if one or more neighboring pixels are also defective, the compensation becomes erroneous
Solution Approach 1:
The patent divides the pixel array into multiple test regions and systematically tests each region to identify defective pixels. By segmenting the detection process into manageable zones, the system can accurately locate defective pixels even when multiple adjacent pixels are defective, preventing erroneous compensation by knowing exactly which pixels need replacement.
Solution Approach 2:
The patent performs preliminary detection of defective pixels before actual image capture. By pre-identifying which pixels are defective through test patterns, the system can prepare compensation data in advance and ensure that only truly defective pixels are compensated, avoiding erroneous replacement of normal pixels.
2Reliability
If neighboring pixels are used to compensate for defective pixels, then compensation is possible, but normal pixels with high luminance levels may be misjudged as defective
Solution Approach 1:
The patent applies different detection criteria to different regions of the pixel array. By analyzing local characteristics and using test patterns specific to each region, the system can distinguish between normal pixels with high luminance and actual defective pixels, preventing misjudgment while maintaining accurate compensation where needed.
Solution Approach 2:
The patent uses test patterns and compares the response of pixels to these patterns to determine defectiveness. By providing feedback through controlled test conditions, the system can accurately differentiate between normal high-luminance pixels and defective pixels, ensuring only the latter are compensated.
3Measurement precision
If multiple neighboring pixels are tested to determine defectiveness, then accurate detection is possible, but the complexity of the detection process increases
Solution Approach 1:
The patent segments the pixel array into multiple test regions and applies systematic testing to each. This segmentation allows the complex detection process to be broken down into manageable steps, making the increased complexity more manageable while maintaining high detection accuracy through structured analysis of multiple neighboring pixels.
Data Source
AI summary
Pixel signals output from an imaging device having pixels arranged in horizontal and vertical directions are compensated if there are pixel defects. Extracted from the pixel signals are: a first signal from a target pixel; second signals from second pixels having the same color as the target pixel; and third signals from third pixels having a different color from the target pixel, the second and third pixels being located as close to the target pixel on both sides thereof in each direction. Extracted from the second signals are a highest-level signal having the highest luminance level and a second-level signal having the second luminance level. An average luminance level of the second signals is calculated. It is determined whether a particular pixel among the second pixels and causing generation of the highest-level signal is defective by using the highest and average levels. The highest-level signal is selected when the particular pixel is not defective, otherwise, the second-level signal. It is determined whether the target pixel is defective by using the levels of the first and selected signals. The first signal is output when the target pixel is not defective, otherwise, the selected signal.