TANet: Transmission and atmospheric light driven enhancement of underwater images

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dc.authoridLin, Zifan/0000-0002-7046-3102
dc.authoridAlhudhaif, Adi/0000-0002-7201-6963
dc.contributor.authorZhang, Dehuan
dc.contributor.authorGuo, Yakun
dc.contributor.authorZhou, Jingchun
dc.contributor.authorZhang, Weishi
dc.contributor.authorLin, Zifan
dc.contributor.authorPolat, Kemal
dc.contributor.authorAlenezi, Fayadh
dc.date.accessioned2024-09-25T19:57:29Z
dc.date.available2024-09-25T19:57:29Z
dc.date.issued2024
dc.departmentAbant İzzet Baysal Üniversitesien_US
dc.description.abstractMotivated by the adverse impact of light attenuation and scattering, which leads to color distortion and low contrast in underwater images, our study primarily focuses on enhancement techniques for these images using localized transmission feature analysis and global atmospheric light feature extraction. To this end, we propose a novel approach, named TANet, drawing upon the dynamics of transmission and atmospheric light. TANet integrates two primary components: a spatial domain-based Transmission-Driven Refinement module (TDR) and a frequency domain-based Atmospheric Light Removal Fourier Module (ALRF). The TDR module employs a Gated Multipurpose Unit with dual branches, selectively regulating input features. This allows for a refined merging of feature vectors that subsequently interact, enabling cross-channel feature integration. Capitalizing on the correlation between transmission and image quality, TDR facilitates the detailed enhancement of underwater images by depicting the perceived transmission across distinct image sections. Given that atmospheric light exhibits different attenuation rates under water due to varying wavelengths, and considering that atmospheric light is globally constant, thereby influencing underwater image capture, we developed the ALRF module. This caters to the processing of global information within the frequency domain, efficiently negating atmospheric light's impact on underwater images and enhancing their quality and visibility. Our TANet's superior performance is affirmed by extensive experimental results, demonstrating its effectiveness in underwater image enhancement.en_US
dc.description.sponsorshipNational Natural Science Foundation of China [62301105, 61702074]; Liaoning Provincial Natural Science Foundation of China [20170520196]; Fundamental Research Funds for the Central Universities, China [3132019205, 3132019354]; Cultivation Program for the Excellent Doctoral Dissertation of Dalian Maritime University, Chinaen_US
dc.description.sponsorshipThis work was supported in part by the National Natural Science Foundation of China (No. 62301105 and 61702074) , the Liaoning Provincial Natural Science Foundation of China (No. 20170520196) , the Fundamental Research Funds for the Central Universities, China (Nos.3132019205 and 3132019354) , and the Cultivation Program for the Excellent Doctoral Dissertation of Dalian Maritime University, China.en_US
dc.identifier.doi10.1016/j.eswa.2023.122693
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.scopus2-s2.0-85178125589en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2023.122693
dc.identifier.urihttps://hdl.handle.net/20.500.12491/13452
dc.identifier.volume242en_US
dc.identifier.wosWOS:001133012800001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorAlhudhaif, Adi
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzYK_20240925en_US
dc.subjectConvolutional neural networken_US
dc.subjectUnderwater image enhancementen_US
dc.subjectScattering removalen_US
dc.subjectGated multipurpose uniten_US
dc.titleTANet: Transmission and atmospheric light driven enhancement of underwater imagesen_US
dc.typeArticleen_US

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