COMPARISON OF UNDERWATER IMAGE PROCESSING AND RESTORATION USING SEA- THRU AND HAZE-LINES ALGORITHM
Keywords:
Sea-Thru, Haze-Lines, restoration, image, underwaterAbstract
The picture which is taken without good lighting will have a shortcoming such as low contrast and discoloration. The lack of light received by objects is usually affected by the position of the object that might be out of camera range or disturbed by fog or water. In this research, we compare image processing and restoration algorithms to restore underwater images that have low contrast and discoloration compared to the real object. The sample images that we use in this restoration process are taken from the Sea-Thru dataset. The results of this research will display the results of the restoration of each algorithm and analyze the comparison of color restoration, transmission restoration, air-light estimation, and counting the RGB channel. With all comparisons, the strengths and weaknesses of the Sea-Thru and Haze-Lines algorithms will be shown, which are the Sea-Thru result is more successful in displaying object colors clearly but still has shortcomings when the angle of sampling image is down, while the Haze-Lines result has more stable in any angles of sampling image.
Downloads
References
Akkaynak, D. and T. Treibitz. Sea-thru: A method for removing water from underwater images. in Conference on Computer Vision and Pattern Recognition. 2019. DOI: https://doi.org/10.1109/CVPR.2019.00178.
Berman, D., et al., Underwater single image color restoration using haze-lines and a new quantitative dataset. IEEE transactions on pattern analysis and machine intelligence, 2020. 43(8): p. 2822-2837 DOI: https://doi.org/10.1109/TPAMI.2020.2977624.
Zhang, L., et al., A wireless communication scheme based on space-and frequency-division multiplexing using digital metasurfaces. Nature electronics, 2021. 4(3): p. 218-227 DOI: https://doi.org/10.1038/s41928-021-00554-4.
Tan, L.K., Image file formats. Biomed Imaging Interv J, 2006. 2(1): p. e6 DOI: https://doi.org/10.2349/biij.2.1.e6.
BermanD, T., AvidanS. Non localimagedehazing. 2016IEEEConferenceonComputerVisionandPat ternRecognition (CVPR). IEEE, 2016 DOI: https://doi.org/10.1109/CVPR.2016.185.
Steiner, T., et al., European Stroke Organization guidelines for the management of intracranial aneurysms and subarachnoid haemorrhage. Cerebrovascular diseases, 2013. 35(2): p. 93-112 DOI: https://doi.org/10.1159/000346087.
Berman, D., T. Treibitz, and S. Avidan. Air-light estimation using haze-lines. 2019. IEEE DOI: https://doi.org/10.1109/ICCPHOT.2017.7951489.
Riaz, S., et al., Visibility Restoration Using Generalized Haze-Lines. Inf. Technol. Control., 2021.50(1): p. 188-207 DOI: https://doi.org/10.5755/j01.itc.50.1.27900.
Dollár, P. and C.L. Zitnick. Structured forests for fast edge detection. 2018. DOI: https://doi.org/10.1109/ICCV.2013.231.
Jerlov, N.G., Marine optics. 1976: Elsevier.
Berman, N., et al., This mine is mine! How minerals fuel conflicts in Africa. American Economic Review, 2017. 107(6): p. 1564-1610 DOI: https://doi.org/10.1257/aer.20150774.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Author
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
