2D-GAN: Dual-Decoding Generative Adversarial Networks for Infrared Image Enhancement

2D-GAN: Dual-Decoding Generative Adversarial Networks for Infrared Image Enhancement | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article 2D-GAN: Dual-Decoding Generative Adversarial Networks for Infrared Image Enhancement Yang Yu, Lin Jiang, Qijun Hu, Qiang Zeng, Xin Sun This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5015889/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Infrared imaging technology finds wide application across various fields, yet suffers from issues such as atmospheric thermal radiation interference, resulting in poor contrast, blurred details, and noise in infrared images. Consequently, enhancing infrared images is essential as a preprocessing step to obtain high-quality data. This paper proposes an infrared image enhancement algorithm based on Dual-Decoding Generative Adversarial Networks(2D-GAN) to address these challenges.The proposed algorithm employs a two-step decoding structure within the 2D-GAN framework to enhance the network's capability to comprehend and represent input data effectively. Internal and external skip connections are incorporated to bolster the network's perceptual ability, addressing the loss of detailed information during the encoding and decoding processes. Additionally, a cross-level attention module is designed to dynamically allocate positional weights to feature maps, thereby enhancing the natural appearance of the generated images.The effectiveness of the 2D-GAN-based enhancement algorithm is validated through comparative experiments, supplemented by ablation studies that delineate the contributions of each module within the network. Experimental results demonstrate significant enhancement in infrared image quality, affirming the efficacy of the proposed algorithm. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 24 Feb, 2025 Reviews received at journal 14 Feb, 2025 Reviewers agreed at journal 07 Feb, 2025 Reviews received at journal 17 Jan, 2025 Reviewers agreed at journal 17 Jan, 2025 Reviewers invited by journal 15 Jan, 2025 Editor assigned by journal 10 Dec, 2024 Editor invited by journal 05 Sep, 2024 Submission checks completed at journal 04 Sep, 2024 First submitted to journal 02 Sep, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5015889","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":360705251,"identity":"0b9bfcc3-e272-42c1-a565-277312af1340","order_by":0,"name":"Yang Yu","email":"","orcid":"","institution":"School of Computer Science and Software Engineering, Southwest Petroleum University","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Yu","suffix":""},{"id":360705252,"identity":"e3a3f90e-d38b-4044-8952-cb55adde115b","order_by":1,"name":"Lin Jiang","email":"","orcid":"","institution":"School of Computer Science and Software Engineering, Southwest Petroleum University","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Jiang","suffix":""},{"id":360705253,"identity":"8faf8595-59f5-4b2b-94e4-c773192f5e8f","order_by":2,"name":"Qijun Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYBACAyA+IAFhMz5IqKghTQuzwYMzx4jTAgNskg9bmAlrMZdI3njAsu2OvcHtHrOKxAY2Bv727gS8WixnpBUckGx7lrjhzhmzG4k7ZBgkzpzdgN9hN3IMgFoOJ5jdyAFqOcPGYCCRS5wWe5CWgsQ2ZuK1MG4DamEgTsuZZwUHJM4dTtx/51ixRMKZYzyE/XI8efNnibLD9pKzmzd+/FFRI8ff3otfC0gXMzgqofHJQ0g5WAvjByQto2AUjIJRMAowAABk/k/qOsgl+gAAAABJRU5ErkJggg==","orcid":"","institution":"School of Civil Engineering and Geomatics, Southwest Petroleum University","correspondingAuthor":true,"prefix":"","firstName":"Qijun","middleName":"","lastName":"Hu","suffix":""},{"id":360705254,"identity":"adbeba72-43f5-4034-9005-7d843e37c31b","order_by":3,"name":"Qiang Zeng","email":"","orcid":"","institution":"School of Computer Science and Software Engineering, Southwest Petroleum University","correspondingAuthor":false,"prefix":"","firstName":"Qiang","middleName":"","lastName":"Zeng","suffix":""},{"id":360705255,"identity":"59ab8b16-9fb0-491c-b78e-e0e27eeb00dc","order_by":4,"name":"Xin Sun","email":"","orcid":"","institution":"School of Computer Science and Software Engineering, Southwest Petroleum University","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2024-09-02 06:41:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5015889/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5015889/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-06538-0","type":"published","date":"2025-07-01T15:57:34+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86180047,"identity":"42a62ae3-7ebe-4267-8342-0fc6c5670e35","added_by":"auto","created_at":"2025-07-07 16:21:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1221420,"visible":true,"origin":"","legend":"","description":"","filename":"2DGAN.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5015889/v1_covered_ff268109-ff7a-4325-9685-d12d7ea3472b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"2D-GAN: Dual-Decoding Generative Adversarial Networks for Infrared Image Enhancement","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5015889/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5015889/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Infrared imaging technology finds wide application across various fields, yet suffers from issues such as atmospheric thermal radiation interference, resulting in poor contrast, blurred details, and noise in infrared images. Consequently, enhancing infrared images is essential as a preprocessing step to obtain high-quality data. This paper proposes an infrared image enhancement algorithm based on Dual-Decoding Generative Adversarial Networks(2D-GAN) to address these challenges.The proposed algorithm employs a two-step decoding structure within the 2D-GAN framework to enhance the network's capability to comprehend and represent input data effectively. Internal and external skip connections are incorporated to bolster the network's perceptual ability, addressing the loss of detailed information during the encoding and decoding processes. Additionally, a cross-level attention module is designed to dynamically allocate positional weights to feature maps, thereby enhancing the natural appearance of the generated images.The effectiveness of the 2D-GAN-based enhancement algorithm is validated through comparative experiments, supplemented by ablation studies that delineate the contributions of each module within the network. Experimental results demonstrate significant enhancement in infrared image quality, affirming the efficacy of the proposed algorithm.","manuscriptTitle":"2D-GAN: Dual-Decoding Generative Adversarial Networks for Infrared Image Enhancement","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-04 18:08:33","doi":"10.21203/rs.3.rs-5015889/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-24T19:02:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-14T09:47:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"191370967712873092766878729303801560895","date":"2025-02-07T05:30:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-17T15:33:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211494526265515343140249104228874941732","date":"2025-01-17T15:00:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-15T11:25:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-12-11T04:14:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-09-05T17:41:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-04T05:40:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-09-02T06:39:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"994f1d35-162a-4e32-a01e-60a750f75d2d","owner":[],"postedDate":"October 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-07T16:14:14+00:00","versionOfRecord":{"articleIdentity":"rs-5015889","link":"https://doi.org/10.1038/s41598-025-06538-0","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-07-01 15:57:34","publishedOnDateReadable":"July 1st, 2025"},"versionCreatedAt":"2024-10-04 18:08:33","video":"","vorDoi":"10.1038/s41598-025-06538-0","vorDoiUrl":"https://doi.org/10.1038/s41598-025-06538-0","workflowStages":[]},"version":"v1","identity":"rs-5015889","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5015889","identity":"rs-5015889","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}