Acknowledgement
This work was supported by Youngsan University Research Fund of 2024.
References
- L. Cai, N. E. McGuire, R. Hanlon, T. A. Mooney, and Y. Girdhar, "Semi-supervised Visual Tracking of Marine Animals Using Autonomous Underwater Vehicles," International Journal of Computer Vision, Mar. 2023.
- D. R. Yoerger, A. F. Govindarajan, J. C. Howland, J. K. Llopiz, P. H. Wiebe, M. Curran, J. Fujii, D. Gomez-Ibanez, K. Katija, B. H. Robison, B. W. Hobson, M. Risi, and S. M. Rock, "A hybrid underwater robot for multidisciplinary investigation of the ocean twilight zone," Science Robotics, vol. 6, no. 55, June 2021.
- Q.-Y. Zhou and V. Koltun, "Color map optimization for 3D reconstruction with consumer depth cameras," ACM Transactions on Graphics, vol. 33, no. 4, pp. 155:1-155:10, July 2014. https://doi.org/10.1145/2601097.2601134
- K. De and M. Pedersen, "Impact of Colour on Robustness of Deep Neural Networks," in 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). Montreal, BC, Canada: IEEE, Oct. 2021, pp. 21-30.
- D. Akkaynak and T. Treibitz, "Sea-Thru: A Method for Removing Water From Underwater Images," in 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Long Beach, CA, USA: IEEE, June 2019, pp. 1682-1691.
- D. Akkaynak and T. Treibitz, "A Revised Underwater Image Formation Model," in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City, UT: IEEE, June 2018, pp. 6723-6732.
- S. Jamieson, J. P. How and Y. Girdhar. "DeepSeeColor: Realtime Adaptive Color Correction for Autonomous Underwater Vehicles via Deep Learning Methods." In IEEE International Conference on Robotics and Automation, 2023, pp. 3095-3101.
- W. S. Pegau, D. Gray, and J. R. V. Zaneveld, "Absorption and attenuation of visible and nearinfrared light in water: Dependence on temperature and salinity," Applied Optics, vol. 36, no. 24, Aug. 1997.
- N. Carlevaris-Bianco, A. Mohan, and R. M. Eustice, "Initial results in underwater single image dehazing," in OCEANS 2010 MTS/IEEE SEATTLE, Sept. 2010, pp. 1-8.
- H.-Y. Yang, P.-Y. Chen, C.-C. Huang, Y.-Z. Zhuang, and Y.-H. Shiau, "Low Complexity Underwater Image Enhancement Based on Dark Channel Prior," in 2011 Second International Conference on Innovations in Bio-inspired Computing and Applications, Dec. 2011, pp. 17-20.
- J. Y. Chiang and Ying-Ching Chen, "Underwater Image Enhancement by Wavelength Compensation and Dehazing," IEEE Transactions on Image Processing, vol. 21, no. 4, pp. 1756- 1769, Apr. 2012. https://doi.org/10.1109/TIP.2011.2179666
- D. Berman, T. Treibitz, and S. Avidan, "Diving into haze-lines: Color restoration of underwater images," in Proceedings of the British Machine Vision Conference. BMVA Press, 2017.
- M. Bryson, M. Johnson-Roberson, O. Pizarro, and S. B. Williams, "True Color Correction of Autonomous Underwater Vehicle Imagery," Journal of Field Robotics, vol. 33, no. 6, pp. 853-874, 2016. https://doi.org/10.1002/rob.21638
- J. Kim, N. Kim, "Adversarial Learning-Based Image Correction Methodology for Deep Learning Analysis of Heterogeneous Images," KIPS Trans. Software and Data Engineering, Vol.10, No.11, pp.457-464, 2021. https://doi.org/10.3745/KTSDE.2021.10.11.457
- DGK, "Complete Guide to Using the DKC-Pro Color Chart" [Online]. Available: https://dgkcolor.tools/wp-content/uploads/2019/09/Complete-Guide-to-the-DKC-Pro-ColorChart_Final.pdf.