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Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor.

Heegwang Kim1, Jinho Park2, Hasil Park3

  • 1Department of Image, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea. heegwang27@gmail.com.

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|December 14, 2017
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Summary

This study introduces a dual camera stereo image defogging algorithm. The method effectively removes fog from images without distorting colors, enhancing video analysis.

Keywords:
defoggingdehazingimage enhancementimage restorationstereo image processing

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Area of Science:

  • Computer Vision
  • Image Processing

Background:

  • Stereo imaging techniques are increasingly vital for video analysis.
  • Defogging algorithms are crucial for improving visibility in adverse weather conditions.

Purpose of the Study:

  • To present a novel dual camera-based stereo image defogging algorithm.
  • To enhance image quality for outdoor video analysis and dual-camera systems.

Main Methods:

  • Optical flow estimation from stereo foggy image pairs.
  • Generation of initial disparity and transmission maps.
  • Atmospheric light estimation using color line theory.
  • Iterative refinement of the transmission map for defogging.

Main Results:

  • Successful removal of fog from stereo images.
  • Preservation of original colors without distortion.
  • Demonstrated effectiveness in experimental evaluations.

Conclusions:

  • The proposed stereo image defogging method is effective and robust.
  • It serves as a valuable pre-processing step for outdoor video analysis.
  • The algorithm is suitable for dual-camera smartphones.