Adaptive CMS ALU Logic for Low-Noise Image Sensor Readout
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Solution Overview
Problem
Existing image sensors face challenges in achieving high dynamic range and reduced readout noise, particularly in varying lighting conditions, while also maintaining efficient readout periods and frame rates.
Innovation Solution
The implementation of an adaptive correlated multiple sampling (CMS) logic circuit within arithmetic logic units (ALUs) of the image sensor, which determines whether a signal is small or large and adjusts the sampling calculations accordingly, thereby preserving the benefits of CMS while reducing readout periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If correlated multiple sampling (CMS) is applied to reduce readout noise, then measurement precision is improved, but readout period increases and frame rate decreases
Solution Approach 1:
The system dynamically adjusts the sampling mode based on signal intensity. For bright pixels, traditional CMS is used with multiple samples. For dark pixels, adaptive CMS reduces sampling to minimize readout period while maintaining noise reduction benefits. This dynamic adaptation resolves the contradiction by optimizing the trade-off between measurement precision and productivity based on actual signal conditions.
Solution Approach 2:
The patent changes the sampling parameter adaptively based on signal intensity. When pixels are detected to be in dark conditions, the sampling rate and number of samples are reduced compared to bright conditions. This parameter change allows the system to maintain measurement precision for dark pixels without incurring the full readout period penalty of traditional CMS, thereby preserving frame rate.
2Measurement precision
If traditional CMS is used for all pixels, then readout noise is reduced in dark conditions, but readout period increases unnecessarily for bright conditions
Solution Approach 1:
The patent applies different sampling strategies to different spatial regions (pixels) based on their local signal intensity characteristics. Bright pixels receive traditional CMS treatment while dark pixels receive adaptive CMS with reduced sampling. This local quality approach ensures that readout noise is reduced only where necessary (dark conditions) without incurring unnecessary readout period extensions for bright pixels.
Solution Approach 2:
Instead of applying full CMS to all pixels, the system applies partial CMS only to dark pixels where it is actually needed. This partial action eliminates the excessive readout period penalty that would result from applying full CMS uniformly across all pixels, while still achieving the desired noise reduction in the specific region (dark pixels) where it provides benefit.
3Measurement precision
If adaptive CMS logic circuit is implemented, then readout noise reduction is achieved in dark conditions while maintaining frame rate, but device complexity increases
Solution Approach 1:
The patent introduces an adaptive CMS logic circuit as an intermediary component that sits between the pixel array and the readout circuitry. This logic circuit analyzes signal intensity and dynamically controls the sampling process. While this adds device complexity, it enables the system to achieve both readout noise reduction in dark conditions and frame rate maintenance by intelligently adjusting sampling based on actual scene conditions.
Solution Approach 2:
The adaptive CMS logic circuit implements feedback by continuously monitoring pixel signal intensity and adjusting the sampling strategy accordingly. This feedback mechanism allows the system to achieve readout noise reduction only when and where needed (dark conditions), thereby maintaining frame rate. The feedback-based adaptation justifies the added device complexity by providing dynamic optimization that static CMS cannot achieve.
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 readout noise in dark conditions and maintains signal-to-noise ratio in bright conditions, while also reducing readout periods and preserving frame rates.
Implementation Method 1
The image sensor includes an array of pixels having photosensitive elements (e.g., photodiodes) that absorb a portion of the incident image light and generate image charge upon absorption of the image light
Data Source
AI summary
An arithmetic logic unit (ALU) includes a front end latch stage coupled to a Gray code (GC) generator to latch GC outputs, a signal latch stage coupled to latch outputs of the front end latch stage, a GC to binary stage coupled to generate a binary representation of the GC outputs, an adder stage including first inputs coupled to receive outputs of the GC to binary stage, a pre-latch stage coupled to latch outputs of the adder stage, and a feedback latch stage coupled to latch outputs of the pre-latch stage in response to a feedback latch enable signal. The feedback latch enable signal is one of a correlated multiple sampling (CMS) feedback enable signal and a non-CMS feedback enable signal. The ALU is configured to perform CMS calculations in response to the CMS feedback enable signal and perform non-CMS calculations in response to the non-CMS feedback enable signal.