Single Row Defective Pixel Correction in Image Sensors
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Solution Overview
Problem
Conventional image sensors face performance and yield issues due to defective pixels, which fail to sense light correctly, leading to inconsistent electrical signals across neighboring pixels.
Innovation Solution
An image processor selects a single row of pixels to detect and recover defective pixels by estimating intensity values, using filters like 'minimum of maximum' or 'maximum of minimum' to replace actual values, reducing storage, processing time, and circuitry costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional image sensors use all pixels for image capture, then image coverage is maximized, but defective pixels cause performance degradation and yield issues
Solution Approach 1:
The patent applies preliminary action by detecting and flagging defective pixels before final image processing. The system performs initial defect detection on captured images, identifies pixels with abnormal intensity values, and marks them for correction before the image is fully processed or stored, preventing defective data from propagating through subsequent processing stages.
Solution Approach 2:
The patent implements discarding and recovering by replacing intensity values from defective pixels with corrected values derived from neighboring pixels. The system discards unreliable data from defective pixels and recovers accurate information by interpolating or copying values from adjacent functional pixels, thus recovering image quality without requiring physical pixel replacement.
2Reliability
If defective pixels are detected and corrected using traditional methods, then image quality is improved, but storage requirements, processing time, and circuitry costs increase
Solution Approach 1:
The patent applies local quality by focusing defect detection and correction only on specific problematic pixels rather than processing the entire image uniformly. The system identifies individual defective pixels and applies correction algorithms locally to those specific locations, leaving the rest of the image processing unchanged. This localized approach reduces overall computational burden and resource requirements.
Solution Approach 2:
The patent implements partial action by performing defect detection on a subset of pixels (only those suspected of being defective) rather than analyzing every pixel in the image. The system uses threshold-based filtering and neighbor comparison to identify candidates for correction, applying intensive processing only where necessary, thus reducing total processing time and computational resources while maintaining image quality.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method effectively detects and recovers defective pixels using a single row, minimizing resource requirements while maintaining image quality and detail retention in high-frequency regions.
Implementation Method 1
The photosensitive element converts the light into an electrical signal proportional to the intensity of the light detected
Data Source
AI summary
An image sensor uses a single row of an array of pixels elements to determine whether a pixel is defective and to recover the defective pixel. The image sensor includes a “maximum of minimum” filter to remove a “black” pixel from a raw image. The image sensor also includes a “minimum of maximum” filter to remove a “white” pixel from the raw image.