CMOS Imager Noise Reduction via Sampling Interval Optimization
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Solution Overview
Problem
CMOS imagers face challenges in reducing 1/f noise, particularly in low frequency bands, which hinders the detection of ultra-weak light and low noise generation during photon counting.
Innovation Solution
A semiconductor photodetection device with a pixel circuit that generates reset and exposure signals, an analog-digital conversion unit performing sampling processes at specific intervals, and a detection unit that processes these signals to detect light based on the converted digital signals, where the exposure sampling interval does not exceed twice the reset sampling interval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If photomultiplier tubes are replaced with CMOS imagers for cost reduction, then device cost is reduced, but noise performance and ultra-weak light detection capability deteriorate
Solution Approach 1:
The patent changes the sampling parameters (number of samples, sampling interval) to optimize the noise performance of CMOS imagers. By carefully selecting the sampling interval and performing multiple samples, the system achieves noise reduction that enables ultra-weak light detection, thereby making CMOS imagers a viable replacement for photomultiplier tubes.
Solution Approach 2:
The patent uses digital signal processing techniques that create multiple copies of the signal through repeated sampling, then processes these copies through averaging or other statistical methods to reduce noise. This digital copying and processing approach compensates for the inherently higher noise levels of CMOS imagers compared to photomultiplier tubes.
2Device complexity
If sampling interval is increased to reduce processing load, then processing complexity is reduced, but noise reduction effectiveness deteriorates
Solution Approach 1:
The patent applies partial action by performing a specific number of sampling operations (not too few to be ineffective, not too many to be excessively complex). The sampling interval and number of samples are optimized to achieve adequate noise reduction with reasonable processing complexity, avoiding both insufficient sampling and excessive processing burden.
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 effectively reduces noise in image sensors, enabling the detection of ultra-weak light with improved signal-to-noise ratio and potential replacement of photomultiplier tubes.
Implementation Method 1
pixels convert incident light into electrons using photodiodes
Data Source
AI summary
Noise of signals in an image sensor is reduced. A pixel circuit generates a reset signal of a predetermined initial voltage and an exposure signal of a signal voltage according to an exposure amount of light in order. An analog-digital conversion unit performs a reset sampling process of converting the reset signal into a first digital signal at a predetermined reset sampling interval and an exposure sampling process of converting the exposure signal into a second digital signal at an exposure sampling interval that does not exceed twice the predetermined reset sampling interval in order. A detection unit detects the light based on the first digital signal and a second digital signal.