Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/171824
Title: Non-uniform illumination underwater image restoration via illumination channel sparsity prior
Authors: Hou, Guojia
Li, Nan
Zhuang, Peixian
Li, Kunqian
Sun, Haihan
Li, Chongyi
Keywords: Engineering::Mechanical engineering
Issue Date: 2023
Source: Hou, G., Li, N., Zhuang, P., Li, K., Sun, H. & Li, C. (2023). Non-uniform illumination underwater image restoration via illumination channel sparsity prior. IEEE Transactions On Circuits and Systems for Video Technology. https://dx.doi.org/10.1109/TCSVT.2023.3290363
Journal: IEEE Transactions on Circuits and Systems for Video Technology
Abstract: Underwater image quality is seriously degraded due to the insufficient light in water. Although artificial illumination can assist imaging, it often brings non-uniform illumination phenomenon. To this end, we develop an illumination channel sparsity prior (ICSP) guided variational framework for non-uniform Illumination underwater image restoration. Technically, the illumination channel sparsity prior is built on the observation that the illumination channel of a uniform-light underwater image in HSI color space contains few pixels whose intensity is very low. Then according to the Retinex theory, we design a variational model with L<sub>0</sub> norm term, constraint term, and gradient term, by integrating the proposed ICSP into an extended underwater image formation model. Such three regularizations are effective in enhancing the brightness, correcting color distortion, and revealing structures and fine-scale details. Meanwhile, we exploit a fast numerical algorithm on the base of the alternating direction method of multipliers (ADMM) to accelerate solving this optimization problem. We also collect a benchmark dataset, namely NUID that contains 925 real underwater images of different non-uniform illumination. Extensive experiments demonstrate that our proposed method is effective in terms of quantitative and qualitative comparisons, ablation studies, convergence analysis, and applications. The code and dataset are available at https://github.com/Hou-Guojia/ICSP.
URI: https://hdl.handle.net/10356/171824
ISSN: 1051-8215
DOI: 10.1109/TCSVT.2023.3290363
Schools: School of Mechanical and Aerospace Engineering 
Rights: © 2023 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:MAE Journal Articles

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