Infrared and visible video fusion method based on local differential correlation features and PID control

Infrared and visible video fusion method based on local differential correlation features and PID control | 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 Research Article Infrared and visible video fusion method based on local differential correlation features and PID control Xiaolin Tang, Jun Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4435483/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract The purpose of infrared and visible video fusion is to combine the complementary features of videos from different modalities. Most fusion algorithms ignore the feature associations of adjacent frames and the guidance of the source frames to the fusion process. Therefore, this paper proposes a new fusion method. First, a spatial-domain multi-attribute detail feature extraction model is proposed, which is capable of extracting the base layer, the bright detail layer and the dark detail layer of the source frames separately. Then, we propose an associated feature extraction model for adjacent frames, which improves the spatial continuity of the fused video. Furthermore, an exponential homomorphic filter is proposed, which simultaneously increases the dynamic range and contrast of the source infrared frames to obtain a general salient target extraction model. In the feature fusion stage, a weighted fusion rule based on edge intensity is used in the detail layer. Then we design the controller, transfer function and measurement function separately, so as to construct a closed-loop proportional-integral-derivative (PID) control system to fuse the base layer, which ensures that the fused video maintains more information of the source video. Experiments on public datasets demonstrate that our fusion method outperforms some state-of-the-art algorithms. Infrared video Visible video Associated features Exponential homomorphic filter PID control system Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 17 May, 2024 Submission checks completed at journal 17 May, 2024 First submitted to journal 17 May, 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. 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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-4435483","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":303692359,"identity":"1fe20d1d-6416-4a0e-a7d0-4ff524d6a677","order_by":0,"name":"Xiaolin Tang","email":"","orcid":"","institution":"Southwest University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Xiaolin","middleName":"","lastName":"Tang","suffix":""},{"id":303692360,"identity":"1584d533-4aa1-4657-b2d2-f08c6fa1ac9d","order_by":1,"name":"Jun Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIie3PMQuCQBTAceXgpkeuF4Z9guAdggRJDX2RSrDFoTFoUVyLVj+J84XQVLvQogTR6BBNDekahNfWcP/5/XjvaZpK9YcZ/TIqKnSBGvGhqGRIN/Qynqz8XocdPZ7IEBS+b0KVuZYWOCZIXSZODgPMgGqnZ03G1iBsEXq0tYcMl0DJLq2JZzuihRACPEcc1VvODRHztI1QCshmSGoS3C6BDAGgCyZw2hC6cWUIYyTjIfpA2dHmCUr8Msn16Pp6uZP+Pi7vj/XYaiUf4W/jKpVKpfrSG3rWPvSbFpyRAAAAAElFTkSuQmCC","orcid":"","institution":"Southwest University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Jun","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-05-17 09:00:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4435483/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4435483/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57370692,"identity":"292f0fa3-be54-4e1a-a2cb-8136a5c0245e","added_by":"auto","created_at":"2024-05-29 18:58:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2870763,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4435483/v1_covered_78cbf6f5-e6db-4013-8335-1ad07d908cb4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Infrared and visible video fusion method based on local differential correlation features and PID control","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-visual-computer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tvcj","sideBox":"Learn more about [The Visual Computer](http://link.springer.com/journal/371)","snPcode":"371","submissionUrl":"https://submission.nature.com/new-submission/371/3","title":"The Visual Computer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Infrared video, Visible video, Associated features, Exponential homomorphic filter, PID control system","lastPublishedDoi":"10.21203/rs.3.rs-4435483/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4435483/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe purpose of infrared and visible video fusion is to combine the complementary features of videos from different modalities. 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