Underwater Image Enhancement Based on Global and Local Equalization of Histogram and Dual-Image Multi-Scale Fusion
Underwater images suffer from color cast and low visibility caused by the medium scattering and absorption, which will reduce the use of valuable information from the image. In this paper, we propose a novel method which includes four stages of pixel intensity center regionalization, global equaliza...
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doaj-5e598acf39e64c788aed9d89abb6ce792021-03-30T04:38:24ZengIEEEIEEE Access2169-35362020-01-01812897312899010.1109/ACCESS.2020.30091619139958Underwater Image Enhancement Based on Global and Local Equalization of Histogram and Dual-Image Multi-Scale FusionLinfeng Bai0https://orcid.org/0000-0002-7971-9565Weidong Zhang1https://orcid.org/0000-0003-2495-4469Xipeng Pan2https://orcid.org/0000-0003-2581-0520Chenping Zhao3https://orcid.org/0000-0002-7379-6076School of Information Engineering, Henan Institute of Science and Technology, Xinxiang, ChinaSchool of Information Engineering, Henan Institute of Science and Technology, Xinxiang, ChinaSchool of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, ChinaSchool of Information Engineering, Henan Institute of Science and Technology, Xinxiang, ChinaUnderwater images suffer from color cast and low visibility caused by the medium scattering and absorption, which will reduce the use of valuable information from the image. In this paper, we propose a novel method which includes four stages of pixel intensity center regionalization, global equalization of histogram, local equalization of histogram and multi-scale fusion. Additionally, this method uses a pixel intensity center regionalization strategy to perform centralization of the image histogram on the overall image. Global equalization of histogram is employed to correct color of the image according to the characteristics of each channel. Local equalization of dual-interval histogram based on average of peak and mean values is used to improve contrast of the image according to the characteristics of each channel. Dual-image multi-scale fusion to integrate the contrast, saliency and exposure weight maps of the color corrected and contrast enhanced images. Experiments on variety types of degraded underwater images show that the proposed method produces better output results in both qualitative and quantitative analysis, thus, the proposed method outperforms other state-of-the-art methods.https://ieeexplore.ieee.org/document/9139958/Underwater image enhancementpixel intensity center regionalizationhistogram equalizationmulti-scale fusion |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Linfeng Bai Weidong Zhang Xipeng Pan Chenping Zhao |
spellingShingle |
Linfeng Bai Weidong Zhang Xipeng Pan Chenping Zhao Underwater Image Enhancement Based on Global and Local Equalization of Histogram and Dual-Image Multi-Scale Fusion IEEE Access Underwater image enhancement pixel intensity center regionalization histogram equalization multi-scale fusion |
author_facet |
Linfeng Bai Weidong Zhang Xipeng Pan Chenping Zhao |
author_sort |
Linfeng Bai |
title |
Underwater Image Enhancement Based on Global and Local Equalization of Histogram and Dual-Image Multi-Scale Fusion |
title_short |
Underwater Image Enhancement Based on Global and Local Equalization of Histogram and Dual-Image Multi-Scale Fusion |
title_full |
Underwater Image Enhancement Based on Global and Local Equalization of Histogram and Dual-Image Multi-Scale Fusion |
title_fullStr |
Underwater Image Enhancement Based on Global and Local Equalization of Histogram and Dual-Image Multi-Scale Fusion |
title_full_unstemmed |
Underwater Image Enhancement Based on Global and Local Equalization of Histogram and Dual-Image Multi-Scale Fusion |
title_sort |
underwater image enhancement based on global and local equalization of histogram and dual-image multi-scale fusion |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
Underwater images suffer from color cast and low visibility caused by the medium scattering and absorption, which will reduce the use of valuable information from the image. In this paper, we propose a novel method which includes four stages of pixel intensity center regionalization, global equalization of histogram, local equalization of histogram and multi-scale fusion. Additionally, this method uses a pixel intensity center regionalization strategy to perform centralization of the image histogram on the overall image. Global equalization of histogram is employed to correct color of the image according to the characteristics of each channel. Local equalization of dual-interval histogram based on average of peak and mean values is used to improve contrast of the image according to the characteristics of each channel. Dual-image multi-scale fusion to integrate the contrast, saliency and exposure weight maps of the color corrected and contrast enhanced images. Experiments on variety types of degraded underwater images show that the proposed method produces better output results in both qualitative and quantitative analysis, thus, the proposed method outperforms other state-of-the-art methods. |
topic |
Underwater image enhancement pixel intensity center regionalization histogram equalization multi-scale fusion |
url |
https://ieeexplore.ieee.org/document/9139958/ |
work_keys_str_mv |
AT linfengbai underwaterimageenhancementbasedonglobalandlocalequalizationofhistogramanddualimagemultiscalefusion AT weidongzhang underwaterimageenhancementbasedonglobalandlocalequalizationofhistogramanddualimagemultiscalefusion AT xipengpan underwaterimageenhancementbasedonglobalandlocalequalizationofhistogramanddualimagemultiscalefusion AT chenpingzhao underwaterimageenhancementbasedonglobalandlocalequalizationofhistogramanddualimagemultiscalefusion |
_version_ |
1724181430111567872 |