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author:

Cai, Xiaowen (Cai, Xiaowen.) [1] | Jiang, Nanfeng (Jiang, Nanfeng.) [2] | Chen, Weiling (Chen, Weiling.) [3] (Scholars:陈炜玲) | Hu, Jinsong (Hu, Jinsong.) [4] (Scholars:胡锦松) | Zhao, Tiesong (Zhao, Tiesong.) [5] (Scholars:赵铁松)

Indexed by:

EI Scopus SCIE

Abstract:

Underwater imaging is usually degraded by low contrast or color cast due to light absorption and scattering. This fact limits the accuracy of object recognition in underwater and marine environments. In this article, to address this issue, we propose a CURE-Net that progressively improves degraded underwater images in a coarse-to-fine way. To be specific, our CURE-Net consists of three cascaded subnetworks. The first two subnetworks use attention and gate fusion to learn multiscale contextual information, whereas the third subnetwork preserves fine spatial details. A detail enhancement block and a supervised recovery block are deployed between subnetworks to further improve the recovery of colors and details. Our proposed CURE-Net is extensively evaluated on popular data sets and achieves state-of-the-art performance. Compared with its peers, our method is also more friendly to object recognition-underwater objects are more easily recognized after being processed by our method.

Keyword:

Colored noise Deep learning (DL) Image color analysis image denoising Image enhancement image processing Image restoration Logic gates Task analysis underwater image enhancement (UIE) Visualization

Community:

  • [ 1 ] [Cai, Xiaowen]Fuzhou Univ, Coll Phys & Informat Engn, Fujian Key Lab Intelligent Proc & Wireless Transmi, Fuzhou, Peoples R China
  • [ 2 ] [Jiang, Nanfeng]Fuzhou Univ, Coll Phys & Informat Engn, Fujian Key Lab Intelligent Proc & Wireless Transmi, Fuzhou, Peoples R China
  • [ 3 ] [Chen, Weiling]Fuzhou Univ, Coll Phys & Informat Engn, Fujian Key Lab Intelligent Proc & Wireless Transmi, Fuzhou, Peoples R China
  • [ 4 ] [Hu, Jinsong]Fuzhou Univ, Coll Phys & Informat Engn, Fujian Key Lab Intelligent Proc & Wireless Transmi, Fuzhou, Peoples R China
  • [ 5 ] [Zhao, Tiesong]Fuzhou Univ, Coll Phys & Informat Engn, Fujian Key Lab Intelligent Proc & Wireless Transmi, Fuzhou, Peoples R China

Reprint 's Address:

  • [Zhao, Tiesong]Fuzhou Univ, Coll Phys & Informat Engn, Fujian Key Lab Intelligent Proc & Wireless Transmi, Fuzhou, Peoples R China;;

Email:

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Source :

IEEE JOURNAL OF OCEANIC ENGINEERING

ISSN: 0364-9059

Year: 2023

Issue: 1

Volume: 49

Page: 226-236

3 . 8

JCR@2023

3 . 8 0 0

JCR@2023

ESI Discipline: ENGINEERING;

ESI HC Threshold:35

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 14

SCOPUS Cited Count: 17

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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