Underwater Images Enhancement by Revised Underwater Images Formation Model
In this paper, we proposed the efficient and appealing technique for underwater images enhancement. Underwater images often suffer from haze, color distortion, low contrast and loss of the human acuity due to light scattering and absorption. To tackle these issues, proposed precise model is presente...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9915404/ |
| _version_ | 1811341327633219584 |
|---|---|
| author | Soo-Chang Pei Chia-Yi Chen |
| author_facet | Soo-Chang Pei Chia-Yi Chen |
| author_sort | Soo-Chang Pei |
| collection | DOAJ |
| description | In this paper, we proposed the efficient and appealing technique for underwater images enhancement. Underwater images often suffer from haze, color distortion, low contrast and loss of the human acuity due to light scattering and absorption. To tackle these issues, proposed precise model is presented expressively showed that: (1) the estimation of the transmission map in atmospheric scatter model is divided into two cases, which are more applicable to underwater images in different situations, and make the enhanced results more robust; (2) model not only removes haze but also restores lost colors of underwater images in the image de-hazing step instead of color correction. First, we proposed a revised underwater dehazing model aiming to eliminate the color of water directly while solving the problem of haze in the underwater images. Then proposed color correction method can adaptively address the problem of color shifting without any additional information. Furthermore, we design a multi-scale illumination fusion to reveal more details and low illumination parts of the image. Experimental results demonstrate that our proposed method outperforms other methods significantly with <inline-formula> <tex-math notation="LaTeX">$5\% \sim 77\%$ </tex-math></inline-formula> quantitative improvement on all four evaluation performance indices and shows more obvious detailed underwater images. Our method can be applied to underwater detection and exploration as the pre-processing step. |
| first_indexed | 2024-04-13T18:54:20Z |
| format | Article |
| id | doaj.art-218b9e0803ad45a888eb47e4d42d22f1 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-13T18:54:20Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-218b9e0803ad45a888eb47e4d42d22f12022-12-22T02:34:18ZengIEEEIEEE Access2169-35362022-01-011010881710883110.1109/ACCESS.2022.32133409915404Underwater Images Enhancement by Revised Underwater Images Formation ModelSoo-Chang Pei0https://orcid.org/0000-0003-2448-4196Chia-Yi Chen1https://orcid.org/0000-0001-9116-7065Department of Electrical Engineering, Graduate Institute of Communication Engineering, National Taiwan University, Taipei, TaiwanDepartment of Electrical Engineering, Graduate Institute of Communication Engineering, National Taiwan University, Taipei, TaiwanIn this paper, we proposed the efficient and appealing technique for underwater images enhancement. Underwater images often suffer from haze, color distortion, low contrast and loss of the human acuity due to light scattering and absorption. To tackle these issues, proposed precise model is presented expressively showed that: (1) the estimation of the transmission map in atmospheric scatter model is divided into two cases, which are more applicable to underwater images in different situations, and make the enhanced results more robust; (2) model not only removes haze but also restores lost colors of underwater images in the image de-hazing step instead of color correction. First, we proposed a revised underwater dehazing model aiming to eliminate the color of water directly while solving the problem of haze in the underwater images. Then proposed color correction method can adaptively address the problem of color shifting without any additional information. Furthermore, we design a multi-scale illumination fusion to reveal more details and low illumination parts of the image. Experimental results demonstrate that our proposed method outperforms other methods significantly with <inline-formula> <tex-math notation="LaTeX">$5\% \sim 77\%$ </tex-math></inline-formula> quantitative improvement on all four evaluation performance indices and shows more obvious detailed underwater images. Our method can be applied to underwater detection and exploration as the pre-processing step.https://ieeexplore.ieee.org/document/9915404/Image processingunderwater image enhancementatmosphere scatter modelimage dehazingdark channel prior |
| spellingShingle | Soo-Chang Pei Chia-Yi Chen Underwater Images Enhancement by Revised Underwater Images Formation Model IEEE Access Image processing underwater image enhancement atmosphere scatter model image dehazing dark channel prior |
| title | Underwater Images Enhancement by Revised Underwater Images Formation Model |
| title_full | Underwater Images Enhancement by Revised Underwater Images Formation Model |
| title_fullStr | Underwater Images Enhancement by Revised Underwater Images Formation Model |
| title_full_unstemmed | Underwater Images Enhancement by Revised Underwater Images Formation Model |
| title_short | Underwater Images Enhancement by Revised Underwater Images Formation Model |
| title_sort | underwater images enhancement by revised underwater images formation model |
| topic | Image processing underwater image enhancement atmosphere scatter model image dehazing dark channel prior |
| url | https://ieeexplore.ieee.org/document/9915404/ |
| work_keys_str_mv | AT soochangpei underwaterimagesenhancementbyrevisedunderwaterimagesformationmodel AT chiayichen underwaterimagesenhancementbyrevisedunderwaterimagesformationmodel |