DIRBW-Net: An Improved Inverted Residual Network Model for Underwater Image Enhancement-Reference-Cited by-同舟云学术

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DIRBW-Net: An Improved Inverted Residual Network Model for Underwater Image Enhancement

Published:2024 Issue: Volume:12 Page:75474-75482
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

An Yongli¹,Feng Yan¹,Yuan Na²,Ji Zhanlin¹^ORCID,Ganchev Ivan³^ORCID

Affiliation:

1. College of Artificial Intelligence, North China University of Science and Technology, Tangshan, China

2. Intelligence and Information Engineering College, Tangshan University, Tangshan, China

3. Telecommunications Research Centre (TRC), University of Limerick, Limerick, Ireland

Funder

High Level Talent Support Project of Hebei Province

National Key Research and Development Program of China

Natural Science Foundation of Hebei Province

National Roadmap for Scientific Infrastructure, financially coordinated by the Ministry of Education and Science of Bulgaria

Telecommunications Research Centre (TRC) of the University of Limerick

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10537162.pdf?arnumber=10537162

Reference32 articles.

1. Underwater image enhancement using contrast limited adaptive histogram equalization and layered difference representation

2. Single Underwater Image Enhancement Based on $L_{P}$ -Norm Decomposition

3. Visual Enhancement of Underwater Images Using Transmission Estimation and Multi-Scale Fusion

4. Improved retinex underwater image enhancement algorithm based on HSI model;Jia;Res. Exploration Lab.,2020

5. Underwater Image Enhancement Using White Balance, USM and CLHE

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