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Related Experiment Video

Updated: May 29, 2026

Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging
07:15

Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging

Published on: July 11, 2025

Real-time adaptive contrast enhancement.

P M Narendra1, R C Fitch

  • 1MEMBER, IEEE, Systems and Research Center, Honeywell, Inc., Minneapolis, MN 55413.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary
This summary is machine-generated.

A new recursive filter simplifies adaptive contrast enhancement for imaging sensors. This method preserves local image contrast in scenes with wide dynamic ranges for better interpretation.

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Area of Science:

  • Image processing
  • Computer vision
  • Sensor technology

Background:

  • Limited display dynamic range (20 dB) challenges the visualization of high dynamic range (HDR) scenes (>40 dB).
  • Maintaining local contrast is crucial for interpreting details in images with significant variations in brightness.

Purpose of the Study:

  • To introduce a simplified recursive filter for real-time adaptive contrast enhancement.
  • To enable the display of high dynamic range scenes on limited dynamic range devices without sacrificing local contrast.

Main Methods:

  • Implementation of an adaptive contrast enhancement scheme using a recursive filter.
  • Development of real-time hardware utilizing charge-coupled devices (CCDs).
  • Processing of standard video formats (525 and 875 lines) from various sources.

Main Results:

  • Successful real-time processing of video imagery with large global dynamic ranges.
  • Preservation of essential local contrast for effective image interpretation.
  • Demonstration of the system's capability with diverse video examples.

Conclusions:

  • The recursive filter approach offers an efficient method for real-time adaptive contrast enhancement.
  • The developed hardware effectively handles high dynamic range video on standard displays.
  • This technique significantly improves image interpretation capabilities for imaging sensors.