An Adaptive Reversible Data Hiding Scheme Using Two- Dimensional Histogram Modification

An Adaptive Reversible Data Hiding Scheme Using Two- Dimensional Histogram Modification | 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 An Adaptive Reversible Data Hiding Scheme Using Two- Dimensional Histogram Modification Van-Thanh Huynh, Thai-Son Nguyen, Phuoc-Hung Vo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6469664/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 Reversible data hiding (RDH) has witnessed significant progress and utilized applications across various domains, including medical imaging, military, and cloud computing. This paper proposes an adaptive RDH based on a novel two-dimensional (2-D) prediction error expansion (PEE) and improved pixel value ordering (I-PVO) mapping to enable a useful trade-off between embedding capacity (EC) and image distortion. Using this scheme, the cover image is first processed using a sliding window size of 4 × 4. Then, each window is divided into inner and outer sub-blocks. The inner sub-block statistical characteristics are determined using the standard deviation of the pixels in the outer sub-block. If this standard deviation is below the first specified threshold, a novel 2-D mapping of PEE strategy is employed for data embedding. Conversely, if the standard deviation falls between the first and the second given thresholds, then conventional pairwise I-PVO is used. Blocks that do not satisfy either condition are bypassed, and no secret data is embedded. This adaptive approach allows the RDH scheme to optimally use both PEE and I-PVO techniques, resulting in higher EC and improved image quality compared to previous RDH methods. 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-6469664","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":444738007,"identity":"1da82297-42a5-4e3c-9125-b92d9e480e0b","order_by":0,"name":"Van-Thanh Huynh","email":"","orcid":"","institution":"Tra Vinh University","correspondingAuthor":false,"prefix":"","firstName":"Van-Thanh","middleName":"","lastName":"Huynh","suffix":""},{"id":444738009,"identity":"c6a1a3c3-3819-43c6-9717-b7c4fed2c94a","order_by":1,"name":"Thai-Son Nguyen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYDACCQaGA0BKDsJjI0IHD1SLMQ9JWkAgsYdoLfbSzQ8P/qi4k75fIseA4UPZYQaD2w0EbJE5ZnCY58yz3B6gFsYZ54Ba7hwg5LAEg8OMbYdze3jOGDDzth1mkJyRQEhL+oeDP9sOp/OAtPwlTkuOwQGg4Qk87D0GzEDrGPglCGm5kVMA9Mthw57jbQUHe86l8xDUwj4jffPHHxWH5dmbmTc++FFmLcdGSAsKOACylgT1o2AUjIJRMApwAQALO0EI7S6jsQAAAABJRU5ErkJggg==","orcid":"","institution":"Tra Vinh University","correspondingAuthor":true,"prefix":"","firstName":"Thai-Son","middleName":"","lastName":"Nguyen","suffix":""},{"id":444738011,"identity":"3ac09bb9-2d1b-4c5f-8a49-edf31080583a","order_by":2,"name":"Phuoc-Hung Vo","email":"","orcid":"","institution":"Tra Vinh University","correspondingAuthor":false,"prefix":"","firstName":"Phuoc-Hung","middleName":"","lastName":"Vo","suffix":""}],"badges":[],"createdAt":"2025-04-17 08:23:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6469664/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6469664/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89190595,"identity":"1353b95e-2fbb-46d0-905a-50aee311b192","added_by":"auto","created_at":"2025-08-16 08:46:54","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1263720,"visible":true,"origin":"","legend":"","description":"","filename":"20250417manuscriptAnadaptiveRDHbasedonnovel2DmappingofPEEandIPVO.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6469664/v1_covered_103a972c-4458-48f0-810b-9569e6d6775a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An Adaptive Reversible Data Hiding Scheme Using Two- Dimensional Histogram Modification","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-6469664/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6469664/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eReversible data hiding (RDH) has witnessed significant progress and utilized applications across various domains, including medical imaging, military, and cloud computing. 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