TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Recovery of underwater images based on the attention mechanism and SOS mechanism |
| 영문제목(English Title) |
Recovery of underwater images based on the attention mechanism and SOS mechanism |
| 저자(Author) |
Shiwen Li
Feng Liu
Jian Wei
|
| 원문수록처(Citation) |
VOL 16 NO. 8 PP. 2552 ~ 2570 (2022. 8) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Underwater images usually have various problems, such as the color cast of underwater images due to the attenuation of different lights in water, the darkness of image caused by the lack of light underwater, and the haze effect of underwater images because of the scattering of light. To address the above problems, the channel attention mechanism, strengthen-operate-subtract (SOS) boosting mechanism and gated fusion module are introduced in our paper, based on which, an underwater image recovery network is proposed. First, for the color cast problem of underwater images, the channel attention mechanism is incorporated in our model, which can well alleviate the color cast of underwater images. Second, as for the darkness of underwater images, the similarity between the target underwater image after dehazing and color correcting, and the image output by our model is used as the loss function, so as to increase the brightness of the underwater image. Finally, we employ the SOS boosting module to eliminate the haze effect of underwater images. Moreover, experiments were carried out to evaluate the performance of our model. The qualitative analysis results show that our method can be applied to effectively recover the underwater images, which outperformed most methods for comparison according to various criteria in the quantitative analysis. |
| 키워드(Keyword) |
underwater image
deep learning
gated module
dehazing
attention mechanism
|
| 파일첨부 |
PDF 다운로드
|
