Adaptive Low Light Image Enhancement Based on Retinex Theory

Adaptive Low Light Image Enhancement Based on Retinex Theory | 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 Adaptive Low Light Image Enhancement Based on Retinex Theory Miaomiao Guo, Jiamin Li, Hongping Hu, Peng Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4254744/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aiming at the color distortion and low visibility in the images with low light conditions, we proposed a low light image enhancement algorithm based on Retinex theory.Firstly, the light component is obtained by multi-scale Gaussian fusion and then are refined. Then, two input images are obtained by the brightness enhancement function and contrast enhancement function, respectively, and the white shark optimization algorithm is applied to perform updating the weights of the Gaussian-Laplace pyramids. Again, the two input images derived from the brightness function and contrast enhancement function are fused by Gaussian-Laplace pyramids. Finally, the final enhanced image are obtained from the multiplication between the adjusted lighting component and the reflection component based on Retinex theory.The experimental results show that the proposed method in this paper has better enhancement effects on images captured under uneven lighting and low lighting conditions. Retinex Theory White Shark Optimization Algorithm Color distortion Gaussian Laplace pyramid fusion Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-4254744","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":290803825,"identity":"e5c86494-69ad-420a-9db9-8175b28e98ec","order_by":0,"name":"Miaomiao Guo","email":"","orcid":"","institution":"North University of China","correspondingAuthor":false,"prefix":"","firstName":"Miaomiao","middleName":"","lastName":"Guo","suffix":""},{"id":290803826,"identity":"9b1062b2-168f-44e5-a702-0ea8f606608c","order_by":1,"name":"Jiamin Li","email":"","orcid":"","institution":"North University of China","correspondingAuthor":false,"prefix":"","firstName":"Jiamin","middleName":"","lastName":"Li","suffix":""},{"id":290803829,"identity":"8e42b491-bbef-4bad-b8fe-6de1f37cb6d7","order_by":2,"name":"Hongping Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAApUlEQVRIiWNgGAWjYBACAwkGxgcfKiTk5EnRwmw444yFsWEDCVrYpHnbKhIZDhCrxVy695gE7zyJBMYG5oePbhCjxXLOuWQLyW0SeewMbMbGOUQ57EaO4Q3DbRLFjA08bNLEajGQSJwjkdhwgAQtRhIHG0jTkpds2HBMwtiwmXi/5B58/KemTk6evfnhY6K0MDDwQGlm4pQjaxkFo2AUjIJRgAsAAEE3L5Z0NgKtAAAAAElFTkSuQmCC","orcid":"","institution":"North University of China","correspondingAuthor":true,"prefix":"","firstName":"Hongping","middleName":"","lastName":"Hu","suffix":""},{"id":290803831,"identity":"0bc5c554-c91d-4721-85a6-843541107fd5","order_by":3,"name":"Peng Wang","email":"","orcid":"","institution":"North University of China","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-04-12 01:28:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4254744/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4254744/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56003747,"identity":"b468b52d-dee4-489b-8da3-832a503217f4","added_by":"auto","created_at":"2024-05-07 12:23:30","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1398277,"visible":true,"origin":"","legend":"","description":"","filename":"AdaptiveLowLightImageEnhancementBasedonRetinexTheory.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4254744/v1_covered_37823e34-c9a9-449e-aa53-bcc47a17acc5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Adaptive Low Light Image Enhancement Based on Retinex Theory","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Retinex Theory, White Shark Optimization Algorithm, Color distortion, Gaussian Laplace pyramid fusion","lastPublishedDoi":"10.21203/rs.3.rs-4254744/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4254744/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAiming at the color distortion and low visibility in the images with low light conditions, we proposed a low light image enhancement algorithm based on Retinex theory.Firstly, the light component is obtained by multi-scale Gaussian fusion and then are refined. 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