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Visualizing Visual Adaptation
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Estimation of visibility using a visual image.

Kyung Won Kim1

  • 1Department of Environment and Energy Science, Gyeongju University, 188 Taejong-ro, Gyeongju, Gyeongsangbuk-do, 780-712, Korea, kwkim@gju.ac.kr.

Environmental Monitoring and Assessment
|February 4, 2015
PubMed
Summary
This summary is machine-generated.

A new camera-based technique estimates visual range directly from images, offering an alternative to traditional optical instruments. This image visual range method shows acceptable accuracy for visibility less than 50 km.

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Area of Science:

  • Atmospheric Science
  • Optical Physics
  • Remote Sensing

Background:

  • Optical instruments quantify atmospheric light extinction, converting it to visual range using established formulas.
  • Visibility is defined as the maximum distance for observing a black object against the horizon.

Purpose of the Study:

  • Introduce and evaluate a camera-based visibility monitoring technique to directly estimate visual range from images.
  • Investigate the relationship between image visual range and distance using visual, optical, and geographical monitoring.

Main Methods:

  • Developed an image visual range estimation method using chromatic analysis of visual images.
  • Introduced a visibility estimation formula based on the y-coordinate position in the image.
  • Compared image visual range with optical-based visual range and geographical data.

Main Results:

  • The relationship between image visual range and the y-coordinate in the image was found to be nonlinear.
  • The average relative error for image visual range under 50 km was deemed acceptable.
  • Discrepancies were attributed to image perspective, faint outlines, and assumptions of uniform aerosol distribution.

Conclusions:

  • Camera-based visibility monitoring offers a viable alternative for estimating visual range.
  • The developed image visual range technique shows promise, particularly for distances under 50 km.
  • Further refinement is needed to address errors related to image analysis and atmospheric assumptions.