Defective Pixel Correction Using Dynamic Thresholds
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Solution Overview
Problem
Conventional image processing methods for correcting defective pixels in solid-state image sensors, such as white spots, are inadequate as they rely on weighting techniques that do not effectively account for varying exposure times and pixel value variations, leading to inconsistent correction results.
Innovation Solution
An image processing apparatus and method that detects defective pixels by calculating a pixel value level and comparing it to a threshold determined by brightness, exposure time, and pixel value variation, using surrounding pixel values for interpolation-based correction, allowing for dynamic adjustment of correction based on exposure time and pixel conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional weighting techniques are used to correct defective pixels, then correction processing can be performed, but the correction results become inconsistent when exposure times and pixel value variations change
Solution Approach 1:
The patent implements dynamic threshold adjustment based on exposure time and pixel value variation. The threshold is not fixed but adapts to changing conditions by incorporating exposure time information and calculating pixel value variations across multiple frames. This allows the correction system to maintain consistency across varying shooting conditions while remaining adaptable to different scenarios.
Solution Approach 2:
The patent changes the parameters used for threshold determination from static to dynamic by incorporating exposure time and pixel value variation metrics. The threshold is recalculated based on these parameters, allowing the system to adjust its correction behavior according to the specific shooting conditions, thereby resolving the contradiction between consistency and adaptability.
2Measurement precision
If a fixed threshold is used for defective pixel determination, then the processing is simple, but it cannot accurately identify defective pixels under varying exposure conditions
Solution Approach 1:
The patent transforms the fixed threshold into a dynamic parameter that changes based on exposure time and pixel value variation. By incorporating these additional parameters, the system achieves higher detection accuracy across varying conditions. The complexity increase is justified by the significant improvement in measurement precision for defective pixel identification.
Solution Approach 2:
The patent performs preliminary calculations of pixel value variations and exposure time adjustments before the actual defective pixel determination. This preliminary action prepares the adaptive threshold in advance, allowing the main detection process to use the pre-computed threshold efficiently, thereby managing complexity while maintaining high accuracy.
3Stability of the object's composition
If white spot level is gradually adjusted by weighting previous and current frame levels, then stability is improved, but responsiveness to rapid changes in white spot level deteriorates
Solution Approach 1:
The patent implements a dynamic response mechanism where the threshold adapts to the rate of change in white spot levels. By incorporating temporal information and pixel value variations, the system can respond rapidly to sudden changes while maintaining stability during gradual variations. This dynamic approach resolves the contradiction between stability and response speed.
Solution Approach 2:
The patent uses feedback from pixel value variations across multiple frames to adjust the threshold dynamically. This feedback mechanism allows the system to detect rapid changes in white spot levels and respond appropriately, improving response speed while maintaining overall stability through continuous monitoring and adjustment.
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 approach enables accurate and adaptive correction of defective pixels, ensuring consistent image quality even when white spot levels change rapidly due to varying exposure times or gain settings, improving the reliability of image data from sensors like those used in endoscopes.
Implementation Method 1
image data containing multiple pixel values obtained by performing photoelectric conversion using multiple pixels
Implementation Method 2
by using pixel values of pixels surrounding the determined defective pixel that is to be corrected, interpolate the pixel value of the determined defective pixel that is to be corrected
Data Source
AI summary
An image processing apparatus including a processor including hardware, the processor being configured to: detect a defective pixel from among the multiple pixels; calculate a level of a pixel value of the defective pixel; compare the calculated level of the pixel value of the defective pixel with a threshold to determine whether a defective pixel that is stored in a storage is to be corrected, the threshold being determined based on a brightness that is calculated from pixel values close to a defective pixel and on any one of an exposure time of image data corresponding to a defective pixel on which a determination is to be made, a value of gain, and variation in pixel value among pixels surrounding the defective pixel on which a determination is to be made; and interpolate the pixel value of the determined defective pixel that is to be corrected.