Image Sensor Sample Pixel Groups for Dark Current Noise Correction
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Solution Overview
Problem
Image sensors face challenges due to noise, particularly dark current, which affects image quality, and existing technologies lack efficient methods for correcting these issues across varying temperature ranges.
Innovation Solution
An image sensor system and method that includes a plurality of sample pixel groups with different heat dissipation characteristics and temperature sensors, allowing for temperature measurement and generation of correction data to address dark current noise, including dark level correction values and pedestal correction coefficients for each temperature range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sample pixel groups with different heat dissipation characteristics are used, then temperature measurement precision is improved, but device complexity increases
Solution Approach 1:
The pixel array is divided into multiple sample pixel groups (first sample pixel group, second sample pixel group, etc.), each with different heat dissipation characteristics. Temperature sensors are separately coupled to each group to measure their respective temperatures. This segmentation allows precise temperature measurement across different thermal zones while maintaining a structured, manageable architecture rather than using a single complex temperature sensing system.
2Measurement precision
If temperature-specific correction data is generated for each temperature range, then dark current correction precision is improved, but processing complexity increases
Solution Approach 1:
Correction data is generated for different temperature ranges by utilizing the temperature measurements from sample pixel groups. The system creates temperature-specific correction values (first correction value, second correction value, etc.) that are applied based on the measured temperature. This approach enables precise dark current correction adapted to actual operating conditions while using a systematic parameter-based method rather than complex algorithms.
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 effective correction of dark current noise across different temperature ranges, improving image sensor performance and efficiency by using sample pixel groups and temperature sensors to generate precise correction data.
Implementation Method 1
a plurality of temperature sensors coupled to the sample pixel groups, respectively, to generate temperature detection signals
Implementation Method 2
The photoelectric semiconductor devices may convert light into photo-charge
Data Source
AI summary
Image sensors and image sensor test systems and methods are disclosed. In some implementations, an image sensor may include an active pixel array including a plurality of active pixels operable to convert incident light into pixel signals carrying image information in the incident light, a plurality of sample pixel groups located adjacent to but spatially separate from the active pixel array, and having different heat dissipation characteristics from other sample pixel groups, and a plurality of temperature sensors coupled to the sample pixel groups, respectively, to provide temperature measurements.