Efficient Sky Dehazing by Atmospheric Light Fusion
Jaouad Hajjami1,2, Thibault Napoléon2, Ayman Alfalou2
1Forssea Robotics, 130 rue de Lourmel, 75015 Paris, France.
Sensors (Basel, Switzerland)
|September 3, 2020
Summary
This study introduces an improved image dehazing method using the Koschmieder model. It enhances bright regions and sky colors, achieving better visual quality and higher ZNCC and SSIM scores.
Area of Science:
- Computer Vision
- Image Processing
Background:
- Image dehazing is crucial for restoring visibility in atmospheric conditions.
- Estimating transmission and atmospheric light is challenging due to environmental variability.
Purpose of the Study:
- To present a novel image dehazing method based on the Koschmieder model.
- To improve the restoration of hazy images, particularly in bright regions and sky areas.
Main Methods:
- Utilizes an L0 gradient optimization function with Gaussian filters and an iterative algorithm.
- Employs multiple atmospheric light values and Laplacian/Gaussian pyramids for fusion.
- Enhances contrast to recover sky colors without artifacts.
Main Results:
- The proposed method achieves superior dehazing performance compared to existing techniques.
- Demonstrates higher ZNCC (autocorrelation score) and SSIM (similarity measure) values.
- Results show improved visual quality in dehazed images.
Conclusions:
- The novel approach effectively addresses limitations in transmission and atmospheric light estimation.
- It significantly enhances the dehazing of bright image regions, including the sky.
- The method provides a robust solution for high-quality image restoration in hazy conditions.
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