An Underwater Image Enhancement Algorithm Based on MSR Parameter Optimization
The quality of underwater images is often affected by the absorption of light and the scattering and diffusion of floating objects. Therefore, underwater image enhancement algorithms have been widely studied. In this area, algorithms based on Multi-Scale Retinex (MSR) represent an important research...
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doaj-991b37301a5741b98232a08828f384502021-04-02T05:13:23ZengMDPI AGJournal of Marine Science and Engineering2077-13122020-09-01874174110.3390/jmse8100741An Underwater Image Enhancement Algorithm Based on MSR Parameter OptimizationKai Hu0Yanwen Zhang1Feiyu Lu2Zhiliang Deng3Yunping Liu4School of Automation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaSchool of Automation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaSchool of Automation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaSchool of Automation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaSchool of Automation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaThe quality of underwater images is often affected by the absorption of light and the scattering and diffusion of floating objects. Therefore, underwater image enhancement algorithms have been widely studied. In this area, algorithms based on Multi-Scale Retinex (MSR) represent an important research direction. Although the visual quality of underwater images can be improved to some extent, the enhancement effect is not good due to the fact that the parameters of these algorithms cannot adapt to different underwater environments. To solve this problem, based on classical MSR, we propose an underwater image enhancement optimization (MSR-PO) algorithm which uses the non-reference image quality assessment (NR-IQA) index as the optimization index. First of all, in a large number of experiments, we choose the Natural Image Quality Evaluator (NIQE) as the NR-IQA index and determine the appropriate parameters in MSR as the optimization object. Then, we use the Gravitational Search Algorithm (GSA) to optimize the underwater image enhancement algorithm based on MSR and the NIQE index. The experimental results show that this algorithm has an excellent adaptive ability to environmental changes.https://www.mdpi.com/2077-1312/8/10/741underwater image enhancementMulti-Scale Retinexparameter optimizationno reference image quality assessment |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kai Hu Yanwen Zhang Feiyu Lu Zhiliang Deng Yunping Liu |
spellingShingle |
Kai Hu Yanwen Zhang Feiyu Lu Zhiliang Deng Yunping Liu An Underwater Image Enhancement Algorithm Based on MSR Parameter Optimization Journal of Marine Science and Engineering underwater image enhancement Multi-Scale Retinex parameter optimization no reference image quality assessment |
author_facet |
Kai Hu Yanwen Zhang Feiyu Lu Zhiliang Deng Yunping Liu |
author_sort |
Kai Hu |
title |
An Underwater Image Enhancement Algorithm Based on MSR Parameter Optimization |
title_short |
An Underwater Image Enhancement Algorithm Based on MSR Parameter Optimization |
title_full |
An Underwater Image Enhancement Algorithm Based on MSR Parameter Optimization |
title_fullStr |
An Underwater Image Enhancement Algorithm Based on MSR Parameter Optimization |
title_full_unstemmed |
An Underwater Image Enhancement Algorithm Based on MSR Parameter Optimization |
title_sort |
underwater image enhancement algorithm based on msr parameter optimization |
publisher |
MDPI AG |
series |
Journal of Marine Science and Engineering |
issn |
2077-1312 |
publishDate |
2020-09-01 |
description |
The quality of underwater images is often affected by the absorption of light and the scattering and diffusion of floating objects. Therefore, underwater image enhancement algorithms have been widely studied. In this area, algorithms based on Multi-Scale Retinex (MSR) represent an important research direction. Although the visual quality of underwater images can be improved to some extent, the enhancement effect is not good due to the fact that the parameters of these algorithms cannot adapt to different underwater environments. To solve this problem, based on classical MSR, we propose an underwater image enhancement optimization (MSR-PO) algorithm which uses the non-reference image quality assessment (NR-IQA) index as the optimization index. First of all, in a large number of experiments, we choose the Natural Image Quality Evaluator (NIQE) as the NR-IQA index and determine the appropriate parameters in MSR as the optimization object. Then, we use the Gravitational Search Algorithm (GSA) to optimize the underwater image enhancement algorithm based on MSR and the NIQE index. The experimental results show that this algorithm has an excellent adaptive ability to environmental changes. |
topic |
underwater image enhancement Multi-Scale Retinex parameter optimization no reference image quality assessment |
url |
https://www.mdpi.com/2077-1312/8/10/741 |
work_keys_str_mv |
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