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A closed-loop, all-electronic pixel-wise adaptive imaging system for high dynamic range videography.

Jie Zhang1, Jonathan P Newman1, Xiao Wang2

  • 1Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.

IEEE Transactions on Circuits and Systems. I, Regular Papers : a Publication of the IEEE Circuits and Systems Society
|February 27, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a novel CMOS imaging system with per-pixel adaptive exposure control. This technology enhances image capture in challenging lighting and motion, improving computer vision tasks.

Keywords:
Exposure controlHigh dynamic rangeImage sensorPixel-wise coded imaging

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Area of Science:

  • Computer Vision
  • Image Sensor Technology
  • Integrated Circuits

Background:

  • Traditional digital cameras use global exposure control, leading to motion blur and underexposure in high-variance scenes.
  • Existing solutions for adaptive imaging often involve complex external components, increasing system cost and power consumption.

Purpose of the Study:

  • To develop a CMOS imaging system with per-pixel adaptive exposure and sampling rate control.
  • To overcome the limitations of global exposure control in capturing dynamic and high-contrast scenes.
  • To reduce system complexity and power consumption for adaptive imaging.

Main Methods:

  • Designed a CMOS image sensor with pixel-addressable exposure configurability.
  • Integrated a real-time, per-pixel exposure controller operating in a closed-loop system.
  • Implemented per-pixel exposure control using all-integrated electronics on a 130nm CMOS process.

Main Results:

  • The developed system features pixel-wise adaptive imaging, adjusting exposure and sampling rates locally.
  • The 256x256 pixel chip operates with low power consumption (7.31mW).
  • Successfully captured complex scenes with challenging lighting and motion, outperforming globally-exposed cameras.

Conclusions:

  • Per-pixel adaptive imaging significantly enhances image acquisition in scenes with high brightness and motion variance.
  • The developed system offers a low-complexity, low-power solution for adaptive imaging.
  • This technology provides substantial benefits for computer vision applications like segmentation, motion estimation, and object recognition.