Pixel Defect Detection Circuit Flat Region Confidence Adjustment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image processing pipelines consume significant CPU bandwidth and power when executing software programs for image corrections, leading to inefficient processing of defective pixels in captured images.
Innovation Solution
A pixel defect detection circuit that includes a defect pixel location table, a dynamic defect processing circuit, a flatness detection circuit, and a confidence adjustment circuit to detect and correct defective pixels by updating confidence values only in flat regions, reducing false positives and enhancing reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If software programs are executed on CPU to perform image corrections, then image processing can be performed with flexibility, but CPU bandwidth consumption and power consumption increase significantly
Solution Approach 1:
The patent replaces software-based CPU processing with a dedicated hardware circuit (pixel defect detection circuit) that operates in parallel with the image processing pipeline. This hardware implementation performs defect detection and correction functions that were previously executed as software programs on the CPU, thereby reducing CPU bandwidth consumption and power usage while maintaining processing flexibility through configurable circuit parameters.
2Reliability
If dynamic defect detection is applied to all pixels, then defect detection accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent applies defect detection algorithms selectively based on local image characteristics. The flatness detection circuit identifies regions with uniform pixel values (flat regions) where defect detection is most beneficial, while regions with high variation naturally suppress false positives. This localized approach concentrates processing resources on areas where defect detection provides maximum value, reducing overall processing time while maintaining high detection accuracy.
Solution Approach 2:
Instead of applying full defect detection processing to every pixel in the image, the circuit performs partial processing by first evaluating flatness conditions and only applying the complete defect detection algorithm to pixels in flat regions. This partial action approach reduces computational load and processing time while still achieving reliable defect detection where it matters most.
3Reliability
If confidence values are updated for all pixels, then defect detection reliability improves, but memory bandwidth and processing overhead increase
Solution Approach 1:
The confidence adjustment circuit updates confidence values selectively only for pixels located in flat regions, rather than uniformly updating all pixels in the image. This localized update strategy reduces memory bandwidth consumption and processing overhead while maintaining reliable defect detection coverage in regions where it is most needed. The circuit uses the flatness detection result to gate the confidence update operation, avoiding unnecessary processing in regions where defect detection is less reliable.
Data Source
AI summary
Embodiments relate to a pixel defect detection circuit for detecting and correcting defective pixels in captured image frames. The pixel defect detection circuit includes a defect pixel location table that maps pixel locations in an image frame to respective confidence values, each confidence value indicating a likelihood that a corresponding pixel is defective. The pixel defect detection circuit further includes a dynamic defect processing circuit configured to determine whether a first pixel of an image frame is defective, and a flatness detection circuit configured to determine whether the first pixel is in a flat region of the image frame. The confidence value corresponding to the location of the first pixel is updated based upon whether the first pixel is determined be defective if the first pixel is determined to be in a flat region, and not updated if the first pixel is determined to not be in a flat region.