Defective Pixel Estimation Using High-Sensitivity Pixel Correlation
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Solution Overview
Problem
Conventional technologies face challenges in accurately determining whether a pixel in an image is defective or a pattern with high spatial frequency, leading to difficulties in improving detection accuracy of defective pixels in solid-state imaging devices.
Innovation Solution
An image processing device that includes a defective pixel estimation unit to assess the correlation between high-sensitivity pixels and color pixels, using distribution information and gradient comparisons to estimate pixel defects, and a correction unit to correct identified defective pixels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional defective pixel detection methods are used, then the detection process is simple, but the detection accuracy of defective pixels is low and cannot distinguish between defective pixels and high spatial frequency patterns
Solution Approach 1:
The detection process is segmented into multiple stages: initial defective pixel detection using conventional methods, followed by secondary verification using correlation between high-sensitivity pixels and color pixels. This segmentation allows the system to apply complex analysis only when needed, improving accuracy while controlling overall complexity.
Solution Approach 2:
High-sensitivity pixels are introduced as an intermediary element to verify defective pixel detections. By comparing the correlation between high-sensitivity pixels and color pixels, the system can distinguish true defective pixels from high spatial frequency patterns without directly modifying the original detection algorithm.
2Productivity
If conventional defective pixel correction is applied to all suspicious pixels, then correction speed is fast, but the image quality deteriorates due to erroneous correction of high spatial frequency patterns
Solution Approach 1:
The system performs preliminary verification using high-sensitivity pixel correlation before applying correction. This preliminary action filters out false positives (high spatial frequency patterns) before the correction process, ensuring that only true defective pixels are corrected while maintaining processing efficiency.
Solution Approach 2:
The system uses feedback from high-sensitivity pixel comparisons to verify defective pixel detections before correction. This feedback mechanism ensures that correction is applied only when there is strong evidence of a true defective pixel, improving correction reliability while maintaining speed through efficient verification.
Data Source
AI summary
The present technology relates to an image processing device, an image processing method, and an image processing system capable of improving detection accuracy of a defective pixel. Provided is an image processing device including a defective pixel estimation unit that estimates a defect of a pixel of interest in an image captured by a solid-state imaging device that contains a two-dimensional array of color pixels, and high-sensitivity pixels having higher sensitivity than sensitivities of the color pixels. The defect of the pixel of interest is estimated on the basis of a correlation between pixel values of the high-sensitivity pixels, and pixel values of the color pixels. The image processing device further includes a defective pixel correction unit that corrects the pixel of interest when it is estimated that the pixel of interest is a defective pixel. The present technology is applicable to an image processing device which corrects a defective pixel by signal processing, for example.