Image Sensor Bad Pixel Detection and Correction via Pre-captured Frames
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Solution Overview
Problem
Existing methods for detecting and correcting bad pixels in image sensors lack accuracy and completeness, leading to decreased production yield due to partial bad pixels being treated as defective chips.
Innovation Solution
A method involving the creation and storage of multiple image frames, scanning for bad pixels, storing their locations as bad blocks, and correcting luminance values using a difference ratio-based approach, allowing for accurate detection and correction of bad pixels during image capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If real-time bad pixel correction method is used, then correction speed is improved, but detection accuracy and completeness deteriorate
Solution Approach 1:
The patent performs preliminary actions by capturing multiple image frames before the actual image capture operation. These frames are used to pre-detect and map bad pixels, allowing for accurate identification of bad pixels without requiring real-time detection during the actual capture operation, thus resolving the contradiction between speed and accuracy.
Solution Approach 2:
The patent creates a copy of the image data by capturing multiple frames and storing them in memory. This copied data is then processed to identify bad pixels, allowing the system to perform accurate detection on the copies rather than in real-time during the actual capture operation, thereby improving both detection accuracy and correction completeness.
2Measurement precision
If partial bad pixels are treated as defective chips, then production yield decreases, but detection accuracy is improved
Solution Approach 1:
The patent segments the pixel array into individual pixels and systematically checks each one by comparing luminance values across multiple frames. This segmentation allows for precise identification of only the truly defective pixels, enabling the system to distinguish between partial bad pixels and completely defective chips, thereby improving production yield while maintaining detection accuracy.
Solution Approach 2:
The patent implements a feedback mechanism where the luminance values from multiple captured frames are compared and analyzed. This feedback loop allows the system to identify patterns and determine which pixels are consistently defective across frames, enabling accurate differentiation between partial and complete defects, thus improving both detection accuracy and production yield.
3Measurement precision
If multiple image frames are captured and stored, then detection accuracy is improved, but memory usage and processing time increase
Solution Approach 1:
The patent applies local quality by analyzing only the specific regions or pixels that show abnormal luminance values when comparing frames. Instead of processing the entire image data for every frame, the system focuses computational resources on identifying and correcting only the bad pixels, thereby reducing overall memory usage and processing time while maintaining high detection accuracy.
Data Source
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AI summary
Provided is a method for correcting a bad pixel in an image sensor. The method includes a first step of creating and storing a plurality of image frames of an object; a second step of scanning pixels in the image frames; a third step of storing, when a bad pixel is detected in the image frames, the location of the bad pixel as a bad block location in a memory; and a fourth step of correcting the luminance value of the bad block by calling the bad block location stored in the memory in an image capture operation.