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Circuit Techniques to Improve Low-Light Characteristics and High-Accuracy Evaluation System for CMOS Image Sensor.

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Summary

This study introduces novel column-Analog-to-Digital Converter (ADC) techniques for surveillance cameras, significantly enhancing low-light performance by reducing RUSH current and operating noise. These innovations improve image quality and measurement accuracy in challenging lighting conditions.

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Area of Science:

  • Image Sensors
  • Integrated Circuits
  • Analog-to-Digital Converters

Background:

  • Surveillance cameras require optimized performance in low-light conditions.
  • Simplifying Analog-to-Digital Converters (ADCs) can introduce RUSH current issues.
  • Area reduction is a key design priority for modern imaging systems.

Purpose of the Study:

  • To propose novel column-ADC techniques for enhancing low-light characteristics in surveillance cameras.
  • To address and mitigate RUSH current issues arising from ADC comparator simplification.
  • To develop a high-accuracy evaluation system for low-light optical and electrical signal measurements.

Main Methods:

  • Implemented RUSH current compensation to reduce transient current fluctuations during AD conversion.
  • Utilized timing shift ADCs to decrease the number of simultaneously operating ADCs, minimizing noise.
  • Fabricated test chips using a 55 nm CIS process for experimental validation.

Main Results:

  • Achieved a 63% reduction in low-light linearity degradation.
  • Reduced column interference (RUSH current) by 50%.
  • Demonstrated an inter-sample variation of 0.05 LSB for column interference using the high-accuracy evaluation system.

Conclusions:

  • The proposed techniques effectively improve low-light performance in surveillance cameras by reducing operating noise.
  • The developed ADC architecture offers a figure-of-merit (FoM) of 0.32 e-·pJ/step, proving its utility.
  • The high-accuracy evaluation system validates the effectiveness of the proposed solutions for small signal measurements in low-light scenarios.