Image enhancement algorithm for tunnel construction scenes

Guodong Chen; Han Xu; Yanfei Wu; Haining Xiong; Honglin Mu; Jinxun Lin; Meiling Huang

doi:10.1117/12.3037849

12 September 2024 Image enhancement algorithm for tunnel construction scenes

Guodong Chen, Han Xu, Yanfei Wu, Haining Xiong, Honglin Mu, Jinxun Lin, Meiling Huang

Proceedings Volume 13256, Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024); 132561I (2024) https://doi.org/10.1117/12.3037849
Event: Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024), 2024, Anshan, China

Abstract

Tunnel images are affected by the shooting environment, and there are problems such as uneven light distribution, local occlusion, and more noise, etc. Aiming at the overexposure and distortion of the existing image enhancement algorithms in the optimisation process, we propose a tunnel image enhancement algorithm DNO-SCI (denoising and overexposure suppression based Self- Calibrated illumination). Firstly, based on the SCI model, a noise suppression module based on a priori knowledge is added to effectively suppress the noise of SCI after low-light enhancement. Secondly, overexposure suppression is guided through the Y channel, and finally a lightweight self-calibrated tunnel construction image enhancement algorithm is proposed in combination with depth-separable convolution. Experimental results demonstrate that the proposed image enhancement algorithm can effectively enhance tunnel construction images with uneven brightness and suppress local overexposure.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Guodong Chen, Han Xu, Yanfei Wu, Haining Xiong, Honglin Mu, Jinxun Lin, and Meiling Huang "Image enhancement algorithm for tunnel construction scenes", Proc. SPIE 13256, Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024), 132561I (12 September 2024); https://doi.org/10.1117/12.3037849

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