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author:

Chen, G. (Chen, G..) [1] | Xu, H. (Xu, H..) [2] | Wu, Y. (Wu, Y..) [3] | Xiong, H. (Xiong, H..) [4] | Mu, H. (Mu, H..) [5] | Lin, J. (Lin, J..) [6] | Huang, M. (Huang, M..) [7]

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Scopus

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 SPIE.

Keyword:

Computer version Convolutional neural networks Image enhancement Self-Calibrated illumination Tunnel construction images

Community:

  • [ 1 ] [Chen G.]College of Physics and Information Engineering, Fuzhou Univ., 2 Xueyuan Road, Fujian, Fuzhou, 350108, China
  • [ 2 ] [Xu H.]College of Physics and Information Engineering, Fuzhou Univ., 2 Xueyuan Road, Fujian, Fuzhou, 350108, China
  • [ 3 ] [Wu Y.]China Railway 17th Bureau Group No.6 Engineering Co., 181 Lianjiang Middle Road, Fujian, Fuzhou, 350014, China
  • [ 4 ] [Xiong H.]China Railway 17th Bureau Group No.6 Engineering Co., 181 Lianjiang Middle Road, Fujian, Fuzhou, 350014, China
  • [ 5 ] [Mu H.]Nanping Wusha Expressway Co., 8 Minjiang Road, Fujian, Nanping, 353000, China
  • [ 6 ] [Lin J.]Fujian Shuboxun Information Technology Co., 523 Gongye Road, Fujian, Fuzhou, 350025, China
  • [ 7 ] [Huang M.]College of Physics and Information Engineering, Fuzhou Univ., 2 Xueyuan Road, Fujian, Fuzhou, 350108, China

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ISSN: 0277-786X

Year: 2024

Volume: 13256

Language: English

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 1

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