A real-world underwater image enhancement method based on multi-color space and two-stage adaptive fusion-Reference-Cited by-同舟云学术

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A real-world underwater image enhancement method based on multi-color space and two-stage adaptive fusion

Published:2024-01-07 Issue:3 Volume:18 Page:2135-2149
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Ji Kai,Lei Weimin,Zhang Wei

Funder

Fundamental Research Funds for the Central Universities

‘Jie Bang Gua Shuai’ Science and Technology Major Project of Liaoning Province in 2022

National Key Research and Development Program of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11760-023-02864-w.pdf

Reference51 articles.

1. Jaffe, J.S.: Computer modeling and the design of optimal underwater imaging systems. IEEE J. Ocean. Eng. 15(2), 101–111 (1990)

2. Hu, K., Weng, C., Zhang, Y., Jin, J., Xia, Q.: An overview of underwater vision enhancement: from traditional methods to recent deep learning. J. Mar. Sci. Eng. 10(2), 241 (2022)

3. Jian, M., Liu, X., Luo, H., Lu, X., Yu, H., Dong, J.: Underwater image processing and analysis: a review. Signal Process. Image Commun. 91, 116088 (2021)

4. Anwar, S., Li, C.: Diving deeper into underwater image enhancement: a survey. Signal Process. Image Commun. 89, 115978 (2020)

5. Rathi, D., Jain, S., Indu, S.: Underwater fish species classification using convolutional neural network and deep learning. In: 2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR), pp. 1–6. IEEE (2017)

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