Laser & Optoelectronics Progress, Volume. 60, Issue 2, 0210011(2023)
Single Image Defogging Algorithm Based on Attention Mechanism
Present image-defogging methods have a range of problems: insufficient numbers of real datasets, local contrast imbalance, and defogging image distortion. This paper proposes a novel defogging network model (Densely Resnet with SKattention-Dehaze Net, DRS-Dehaze Net) that mitigates defogging image distortion. First, the fogged image is transformed into a multi-angle feature input map by the preprocessing module. The feature information is then extracted and redistributed through a dense residual architecture with an attention mechanism. Finally, the features are fused to output a fog-free image. Experimental comparison results confirmed a better defogging effect of the proposed algorithm than that of other algorithms. Our model effectively improves the distortion in defogged images and enhances the image clarity to a certain extent.
Get Citation
Copy Citation Text
Ruihu Cao, Pengchao Zhang, Lei Wang, Fan Zhang, Jie Kang. Single Image Defogging Algorithm Based on Attention Mechanism[J]. Laser & Optoelectronics Progress, 2023, 60(2): 0210011
Category: Image Processing
Received: Dec. 14, 2021
Accepted: Mar. 14, 2022
Published Online: Jan. 6, 2023
The Author Email: Zhang Pengchao (8811202@qq.com)