Imaging Device Pixel Defect Diagnosis via Dual Light-Receiving Element Ratio
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Solution Overview
Problem
Current imaging devices face challenges in enhancing the reliability of captured images, particularly due to defects and blooming issues that affect image quality.
Innovation Solution
The implementation of a diagnostic method that utilizes a pair of light-receiving elements within each pixel, generating detection values and performing diagnosis processing based on the ratio between these values to identify and correct defects and blooming, thereby improving image reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single light-receiving element is used per pixel, then the device structure is simple, but the reliability of captured images deteriorates due to defects and blooming
Solution Approach 1:
Each pixel is segmented into multiple light-receiving elements (first and second light-receiving elements) with different sensitivities. This segmentation allows the system to compare signals from elements with different responses to the same light input, enabling defect detection and blooming suppression through ratio calculation, thereby improving image reliability without requiring complex external diagnostic equipment
Solution Approach 2:
Different light-receiving elements within the same pixel are assigned different sensitivities (first element with higher sensitivity, second element with lower sensitivity). This local quality differentiation enables the system to use the ratio of their outputs to detect defects and suppress blooming effects, as the elements respond differently to normal light variations versus defective or blooming conditions
2Reliability
If multiple light-receiving elements are added to each pixel, then image reliability improves through defect detection, but the manufacturing precision requirements worsen
Solution Approach 1:
The pixel structure is pre-configured with multiple light-receiving elements having predetermined different sensitivities during manufacturing. This preliminary arrangement establishes a built-in diagnostic capability that automatically detects defects through ratio comparison, reducing the need for post-manufacturing calibration and compensating for variations in manufacturing precision
Solution Approach 2:
The system changes the sensitivity parameter of light-receiving elements within the same pixel structure. By designing elements with inherently different sensitivities (first element more sensitive, second element less sensitive), the system creates a differential response that is insensitive to manufacturing variations, as both elements experience the same physical conditions but with different gain characteristics
3Reliability
If defect correction is performed using traditional methods, then pixel defects are addressed, but blooming issues remain unresolved
Solution Approach 1:
The system uses feedback from multiple light-receiving elements with different sensitivities to detect both defects and blooming conditions. By comparing the ratio of signals from the first and second light-receiving elements, the system can identify when blooming occurs (indicated by abnormal ratio values) and apply appropriate correction, creating a feedback mechanism that simultaneously addresses both defects and blooming
Solution Approach 2:
The system employs asymmetric response characteristics of light-receiving elements to differentiate between defects and blooming. The first light-receiving element has higher sensitivity while the second has lower sensitivity, creating an asymmetric response pattern that allows the ratio calculation to distinguish between normal light variation, defect conditions, and blooming effects, enabling selective correction
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 enhances the reliability of captured images by accurately detecting and correcting defects and blooming, leading to improved image quality and accuracy.
Implementation Method 1
each having a photodiode are disposed in matrix, and each of the pixels generates an electric signal corresponding to an amount of light reception
Data Source
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AI summary
An imaging device according to the present disclosure includes: a plurality of pixels each including a first light-receiving element and a second light-receiving element, the plurality of pixels including a first pixel; a generating section that is able to generate a first detection value on a basis of a light-receiving result by the first light-receiving element of each of the plurality of pixels, and is able to generate a second detection value on a basis of a light-receiving result by the second light-receiving element of each of the plurality of pixels; and a diagnosis section that is able to perform a diagnosis processing on a basis of a detection ratio that is a ratio between the first detection value and the second detection value in the first pixel.