A Multi-Stage Progressive Network with Feature Transmission and Fusion for Marine Snow Removal
文献类型：期刊论文
| 作者 | Liu, Lixin1,2 ; Liao, Yuyang1,2; He, Bo2; Kwan, Chiman
|
| 刊名 | SENSORS
 |
| 出版日期 | 2024 |
| 卷号 | 24期号:2页码:14 |
| 关键词 | marine snow underwater image processing multi-stage deep learning |
| DOI | 10.3390/s24020356 |
| 英文摘要 | Improving underwater image quality is crucial for marine detection applications. However, in the marine environment, captured images are often affected by various degradation factors due to the complexity of underwater conditions. In addition to common color distortions, marine snow noise in underwater images is also a significant issue. The backscatter of artificial light on marine snow generates specks in images, thereby affecting image quality, scene perception, and subsequently impacting downstream tasks such as target detection and segmentation. Addressing the issues caused by marine snow noise, we have designed a new network structure. In this work, a novel skip-connection structure called a dual channel multi-scale feature transmitter (DCMFT) is implemented to reduce information loss during downsampling in the feature encoding and decoding section. Additionally, in the feature transfer process for each stage, iterative attentional feature fusion (iAFF) modules are inserted to fully utilize marine snow features extracted at different stages. Finally, to further optimize the network's performance, we incorporate the multi-scale structural similarity index (MS-SSIM) into the loss function to ensure more effective convergence during training. Through experiments conducted on the Marine Snow Removal Benchmark (MSRB) dataset with an augmented sample size, our method has achieved significant results. The experimental results demonstrate that our approach excels in removing marine snow noise, with a peak signal-to-noise ratio reaching 38.9251 dB, significantly outperforming existing methods. |
| WOS关键词 | IMAGE ; ALGORITHMS |
| 资助项目 | Strategic Priority Research Program of Chinese Academy of Sciences |
| WOS研究方向 | Chemistry ; Engineering ; Instruments & Instrumentation |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:001151132700001 |
| 资助机构 | Strategic Priority Research Program of Chinese Academy of Sciences |
| 源URL | [http://ir.idsse.ac.cn/handle/183446/10813]  |
| 专题 | 深海工程技术部_深海信息技术研究室 |
| 通讯作者 | Liu, Lixin |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Deep Sea Sci & Engn, Sanya 572000, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Lixin,Liao, Yuyang,He, Bo,et al. A Multi-Stage Progressive Network with Feature Transmission and Fusion for Marine Snow Removal[J]. SENSORS,2024,24(2):14. |
| APA | Liu, Lixin,Liao, Yuyang,He, Bo,&Kwan, Chiman.(2024).A Multi-Stage Progressive Network with Feature Transmission and Fusion for Marine Snow Removal.SENSORS,24(2),14. |
| MLA | Liu, Lixin,et al."A Multi-Stage Progressive Network with Feature Transmission and Fusion for Marine Snow Removal".SENSORS 24.2(2024):14. |
入库方式： OAI收割
来源：深海科学与工程研究所
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