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Image dehazing algorithm based on light-value weighted allocation and multi-layer restricted perception.
Dongyang Shi1, Sheng Huang2,3, Wei Zhao1
1School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.
Scientific Reports
|April 11, 2025
Summary
The DWARP algorithm enhances image dehazing by improving bright region processing and noise resistance. This novel approach achieves superior performance in foggy conditions, benefiting applications like intelligent transportation.
Area of Science:
- Computer Vision
- Image Processing
- Artificial Intelligence
Background:
- Existing image dehazing models struggle with distortions in bright regions and lack robustness to noise.
- Effective dehazing is crucial for applications like intelligent transportation.
Purpose of the Study:
- To propose a novel image dehazing algorithm, DWARP (Dehazing With light-value weighted Allocation and multi-layer Restricted Perception), that addresses limitations in bright region processing and noise robustness.
- To improve the accuracy and efficiency of image dehazing.
Main Methods:
- Developed an atmospheric light estimation module using weighted allocation with a three-stage refinement process.
- Implemented a multi-layer restricted perception scheme for transmittance estimation, transforming bright region distortions into transmittance error reduction.
- Integrated a brightness adjustment module and a Gaussian denoising module to enhance visual quality and noise resistance.
Main Results:
- The DWARP algorithm effectively prevents distortion in bright regions and significantly improves noise robustness.
- Achieved high average performance metrics: PSNR (37.41 dB), SSIM (88.74%), and VIF (0.89) across four datasets.
- Outperformed the RIDCP algorithm in PSNR, SSIM, and VIF, while also enhancing dehazing efficiency.
Conclusions:
- The DWARP algorithm demonstrates scientific and theoretical correctness in its improvements for image dehazing.
- The model effectively handles bright regions like the sky and exhibits strong noise resistance.
- Presents a novel and effective approach for fog removal, advancing fields such as intelligent transportation.
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