Literature DB >> 33820170

Underwater image enhancement method based on adaptive attenuation-curve prior.

Ke Liu, Yongquan Liang.   

Abstract

The attenuation (sum of absorption and scattering), which is caused by the dense and non-uniform medium, generally leads to problems of color degradation and detail loss in underwater imaging. In this study, we describe an underwater image enhancement method based on adaptive attenuation-curve prior. This method uses color channel transfer (CCT) to preprocess the underwater images, light smoothing, and wavelength-dependent attenuation to estimate water light and obtain the attenuation ratio between color channels, and estimates and refines the initial relative transmission of the channel. Additionally, the method calculates the attenuation factor and saturation constraints of the three color channels and generates an adjusted reverse saturation map (ARSM) to address uneven light intensity, after which the image is restored through water light and transmission estimation. Furthermore, we applied white balance fusion globally guided image filtering (G-GIF) technology to achieve color enhancement and edge detail preservation in the underwater images. Comparison experiments showed that the proposed method obtained better color and de-hazing effects, as well as clearer edge details, relative to current methods.

Entities:  

Year:  2021        PMID: 33820170     DOI: 10.1364/OE.413164

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  1 in total

1.  Deep Supervised Residual Dense Network for Underwater Image Enhancement.

Authors:  Yanling Han; Lihua Huang; Zhonghua Hong; Shouqi Cao; Yun Zhang; Jing Wang
Journal:  Sensors (Basel)       Date:  2021-05-10       Impact factor: 3.576

  1 in total

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