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Related Experiment Video

Updated: Jun 25, 2025

Author Spotlight: Non-Invasive Imaging of Complex Bio-Structures Using Polarization-Sensitive Two-Photon Microscopy
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Atmospheric Light Estimation Using Polarization Degree Gradient for Image Dehazing.

Shuai Liu1,2, Hang Li1, Jinyu Zhao1

  • 1Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Dong Nanhu Road 3888, Changchun 130033, China.

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|May 25, 2024
PubMed
Summary

This study introduces a new method for estimating atmospheric light using sky polarization, improving image dehazing. The novel approach enhances existing algorithms, offering superior ambient light estimation for clearer images.

Keywords:
atmospheric light estimationdehazingnear-zero closure interval for polarizationpolarization degree gradient

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Area of Science:

  • Computer Vision
  • Image Processing
  • Optical Physics

Background:

  • Image dehazing techniques often rely on atmospheric light estimation.
  • Current methods lack physical models, reducing accuracy and dehazing effectiveness.

Purpose of the Study:

  • To develop a novel approach for estimating atmospheric light using sky polarization.
  • To enhance existing image dehazing algorithms by integrating the proposed atmospheric light estimation method.

Main Methods:

  • Estimating atmospheric light using the polarization state and polarization degree gradient of the sky.
  • Applying the novel atmospheric light estimation to pre-existing dehazing algorithms.
  • Developing and testing a real-time dehazing system.

Main Results:

  • The proposed approach offers a clear advantage over previous ambient light estimation methods.
  • Significant improvements in dehazing effectiveness were observed.
  • Enhanced criteria include contrast, Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index Measure (SSIM).

Conclusions:

  • The novel polarization-based atmospheric light estimation method effectively enhances image dehazing.
  • The approach provides a significant improvement over existing methods for real-time applications.