Digital Pixel With Extended Dynamic Range Using Correlated Double Sampling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Image sensors face challenges in accurately determining light intensity due to noise sources like thermal noise, comparator offset, and charge leakage, which affect the dynamic range and measurement accuracy, especially in environments with varying light intensities.
Innovation Solution
A pixel cell structure with a photodiode, charge sensing unit, and analog-to-digital converter (ADC) that includes a sampling capacitor and comparator, where the controller sets voltages to cancel reset noise and comparator offset, allowing for effective mitigation of noise through controlled sampling operations, even with extended integration periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the integration period is extended to improve light intensity measurement accuracy, then measurement precision is improved, but noise sources like thermal noise and reset noise increase
Solution Approach 1:
The patent applies preliminary action by performing a reset operation on the charge sensing unit before the integration period to clear residual charge and establish a known initial state. This preliminary reset action prevents residual charge from interfering with the measurement, allowing extended integration periods without accumulating unwanted noise from previous measurements.
Solution Approach 2:
The patent uses feedback through correlated double sampling, where the reset noise is measured during a reset phase and then subtracted from the signal measured during the integration phase. This feedback mechanism allows the system to maintain extended integration periods for improved measurement precision while compensating for the thermal and reset noise that accumulates during those extended periods.
2Adaptability or versatility
If the dynamic range is extended to capture a wider range of light intensities, then adaptability is improved, but measurement accuracy deteriorates due to noise
Solution Approach 1:
The patent segments the measurement process into distinct phases: a reset phase for measuring and storing reset noise, and an integration phase for measuring the signal plus noise. By separating these measurements into different time segments, the system can handle a wide dynamic range while maintaining accuracy through subsequent noise subtraction.
Solution Approach 2:
The correlated double sampling mechanism provides feedback by using the reset phase measurement to compensate for noise in the integration phase measurement. This feedback loop enables the system to maintain measurement accuracy across an extended dynamic range by continuously characterizing and subtracting noise components.
3Measurement precision
If noise cancellation techniques are applied to improve measurement accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent merges the reset operation and signal measurement into a unified correlated double sampling framework. By combining these operations and using the same charge sensing unit and ADC for both phases, the system achieves noise cancellation without requiring separate dedicated circuits, thus limiting the increase in device complexity.
Solution Approach 2:
The charge sensing unit and ADC serve multiple functions: they measure reset noise during the reset phase and measure the signal during the integration phase. This multi-functionality allows the system to implement noise cancellation techniques without adding dedicated measurement circuits, thereby improving measurement precision while controlling device complexity.
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 extends the dynamic range of image sensors, improves measurement accuracy, and enhances performance in applications like virtual reality and augmented reality systems by reducing noise leakage and maintaining high accuracy across a wide range of light intensities.
Implementation Method 1
A typical image sensor includes a photodiode to sense incident light by converting photons into charge (e.g., electrons or holes).
Data Source
AI summary
In one example, an apparatus comprises: a comparator; a sampling capacitor having a first plate and a second plate. The first plate is coupled with an output of a charge sensing unit that senses charge generated by a photodiode, whereas the second plate is coupled with an input of the comparator. The apparatus further includes a controller configured to: at a first time, set a first voltage across the sampling capacitor based on an output voltage of the charge sensing unit; reset the charge sensing unit to set the first plate at a second voltage and to set the second plate at a third voltage based on the first voltage and the second voltage; compare, using the comparator, the third voltage against one or more thresholds; and generate, based on the comparison result, a quantization result of the output voltage of the charge sensing unit at the first time.