Non-uniform illumination underwater image restoration via illumination channel sparsity prior

• Main Authors: Hou, Guojia, Li, Nan, Zhuang, Peixian, Li, Kunqian, Sun, Haihan, Li, Chongyi
• 其他作者: School of Mechanical and Aerospace Engineering
• 格式: Article
• 語言: English
• 出版: 2023
• 主題: Engineering::Mechanical engineering; Non-uniform Illumination; Underwater Image Restoration
• 在線閱讀: https://hdl.handle.net/10356/171824
• 機構: Nanyang Technological University

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 L₀ 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.