| 题名 | Multiple channel adjustment based on composite backbone network for underwater image enhancement |
| 作者 | |
| 通讯作者 | Lu, Dongxin |
| 发表日期 | 2023
|
| DOI | |
| 发表期刊 | |
| ISSN | 1758-0366
|
| EISSN | 1758-0374
|
| 卷号 | 22期号:3页码:162-175 |
| 摘要 | In order to heighten enhancement effects for underwater images under different conditions, multiple channel adjustment based on composite backbone network (MC-CBNet) was proposed that skilfully combine the enhancement effect from RGB colour space as well as HSV and Lab. MC-CBNet consists of a preliminary enhance block, a multi-space adjust block and a confidence map block. Preliminary enhance block and multi-space adjust block adjust the images from RGB, HSV and Lab colour spaces respectively. The confidence map is obtained by the ultimate block to fuse the results of different channels. Besides, preliminary enhance block and confidence map block are formed from composite backbones. Experimental results on underwater image enhancement benchmark (UIEB) indicate that our method gets better grades than existing methods under both reference subset and challenging subset evaluation. Copyright © 2023 Inderscience Enterprises Ltd. |
| 关键词 | |
| 相关链接 | [来源记录] |
| 收录类别 | |
| 语种 | 英语
|
| 学校署名 | 第一
|
| 资助项目 | This research is sponsored by the following funds: 1 Public welfare technology research project of Zhejiang Provinces Science Foundation in China. The effect model Construction and 3D visualisation of auricular point pivot regulation of brain neural (NO. LGF20F020009). 2 Key R&D Program of Zhejiang Province. Research on intelligent service technology and equipment of health and elderly care-Support the research and application development of medical nursing care robot and elderly care service system of internet hospitals (NO. 2020C03107). 3 Shandong Provincial Natural Science Foundation (Grant No. ZR2023QF036 and Grant No. ZR2021MD070). 4 Shenzhen Natural Science Foundation Project: Design of Micro Underwater Unmanned Vehicles and Research on Neural Networks for Underwater Image Processing.
|
| WOS研究方向 | Computer Science
|
| WOS类目 | Computer Science, Artificial Intelligence
; Computer Science, Theory & Methods
|
| WOS记录号 | WOS:001127284400001
|
| 出版者 | |
| EI入藏号 | 20240215355703
|
| EI主题词 | Deep learning
; Underwater imaging
|
| EI分类号 | Ergonomics and Human Factors Engineering:461.4
; Imaging Techniques:746
|
| 来源库 | EV Compendex
|
| 引用统计 |
被引频次[WOS]：1
|
| 成果类型 | 期刊论文 |
| 条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/706279 |
| 专题 | 工学院_系统设计与智能制造学院 工学院_机械与能源工程系 |
| 作者单位 | 1.School of System Design and Intelligent Manufacturing, Southern University of Science and Technology, Shenzhen; 518055, China 2.Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen; 518055, China 3.Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao; 266075, China 4.Health Management System Engineering Center, School of Public Health, Hangzhou Normal University, Hangzhou; 311121, China |
| 第一作者单位 | 系统设计与智能制造学院 |
| 第一作者的第一单位 | 系统设计与智能制造学院 |
| 推荐引用方式 GB/T 7714 |
Chen, Yuhan,Ke, Wende,Kou, Lei,et al. Multiple channel adjustment based on composite backbone network for underwater image enhancement[J]. International Journal of Bio-Inspired Computation,2023,22(3):162-175.
|
| APA |
Chen, Yuhan.,Ke, Wende.,Kou, Lei.,Li, Qingfeng.,Lu, Dongxin.,...&Wan, Junhe.(2023).Multiple channel adjustment based on composite backbone network for underwater image enhancement.International Journal of Bio-Inspired Computation,22(3),162-175.
|
| MLA |
Chen, Yuhan,et al."Multiple channel adjustment based on composite backbone network for underwater image enhancement".International Journal of Bio-Inspired Computation 22.3(2023):162-175.
|
| 条目包含的文件 | 条目无相关文件。 | |||||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
;
修改评论