Multi-Frame Wounded Pixel Detection and Correction
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Solution Overview
Problem
Current defect pixel correction methods cannot effectively detect or correct wounded pixels across multiple frames, leading to image quality degradation by incorrectly removing fine details and edges.
Innovation Solution
A method that receives pixel signals from center and neighboring pixels in multiple frames, determines brightness or color values, and updates defective pixels to the mean of neighboring signals if they exceed specific thresholds, thereby correcting wounded pixels without degrading image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current defect pixel correction methods are used, then dead pixels can be corrected, but wounded pixels cannot be detected or corrected across multiple frames
Solution Approach 1:
The patent applies preliminary action by analyzing pixel brightness across multiple frames before final correction. The system pre-determines which pixels are wounded by comparing brightness values across frames and identifying patterns that indicate defectiveness, enabling correction to be prepared and applied systematically rather than reactively
Solution Approach 2:
The patent transitions from single-frame analysis to multi-frame analysis, adding the temporal dimension to pixel evaluation. By examining brightness values across multiple frames rather than just one, the system gains the ability to distinguish between transient variations and genuine defects, enabling reliable detection of wounded pixels
2Measurement precision
If threshold-based defect detection is applied, then defective pixels can be identified, but fine details and edges are incorrectly removed
Solution Approach 1:
The patent applies dynamics by making the detection threshold adaptive rather than fixed. The system dynamically adjusts the brightness threshold based on the specific pixel location, image content, and multi-frame analysis results. This allows the system to distinguish between genuine defects and valid image features like edges and highlights, preventing their incorrect removal while maintaining accurate defect identification
Solution Approach 2:
The patent applies local quality by treating different regions of the image differently in the correction process. Instead of applying a uniform threshold across the entire image, the system analyzes local characteristics such as pixel neighborhood patterns, image content context, and spatial location to determine appropriate detection criteria for each region, thereby preserving fine details and edges while detecting defects
3Device complexity
If single-frame defect correction is used, then processing is simple, but wounded pixels cannot be reliably detected across multiple frames
Solution Approach 1:
The patent applies merging by combining multiple frame analyses into a unified correction process. Instead of processing frames independently, the system merges the brightness information from multiple frames to create a comprehensive view of pixel behavior over time. This combined analysis enables reliable detection of wounded pixels that would be invisible in single-frame processing, while the systematic approach keeps processing complexity manageable
Data Source
AI summary
A method of defect pixel correction, includes, receiving at least one center pixel signal in a plurality of frames, receiving a plurality of neighboring pixel signals adjacent the center pixel in the plurality of frames, determining a brightness of the center pixel signal, determining the brightness of the plurality of neighboring pixel signals, determining if the brightness of the center pixel signal exceeds a wounded pixel threshold of the plurality of neighboring pixel signals, determining a location of the center pixel having the brightness greater than the wounded pixel threshold in at least one frame, determining a number of reoccurrences of the center pixel having the brightness greater than the wounded pixel threshold, determining if the number of reoccurrences exceeds a defect pixel threshold and updating the at least one center pixel signal to a mean of the plurality of neighboring pixel signals.