Robust Watermarking with PSO and DnCNN

Robust Watermarking with PSO and DnCNN | 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PDF Research Article Robust Watermarking with PSO and DnCNN Ali Amiri, Bahram Kimiaghalam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3885225/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Jun, 2024 Read the published version in Signal, Image and Video Processing → Version 1 posted 7 You are reading this latest preprint version Abstract The NC value obtained for our scheme is very good against jpeg attacks and the results are much better than the compared articles. Also, the NC value obtained for the salt and pepper attack is better than the compared articles. In this paper, an algorithm for multiple watermarking in gray scale images based on contourlet and SVD transforms is presented. Placing a watermark on the S component of the SVD transform of host image is associated with a false positive problem. Different solutions have been proposed, but these solutions themselves face problems such as determining the amount of scaling factor for different images, the undesirable values ​​obtained for robustness to attacks, and most importantly, the low quality of the watermarked image. In the proposed scheme, to solve these problems in the embedding stage, we multiply the Δ value by the host image and multiply the component S obtained from the SVD transform and the SVD is taken from it again using the analysis of the host image by the contourlet and taking the SVD transform from it, and with the help of the PSO transform to find the scaling factor. In the extraction section, contourlet transform is taken from both the host and watermark images and the results are expressed with and without DnCNN. Attack robustness has also been compared with other articles using different images and applying different attacks. The values ​​obtained for false positive in the results section show that this scheme does not have such a problem and is also robust to various attacks. SVD False positive Contourlet PSO DnCNN Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Jun, 2024 Read the published version in Signal, Image and Video Processing → Version 1 posted Editorial decision: Revision requested 02 Feb, 2024 Reviews received at journal 01 Feb, 2024 Reviewers agreed at journal 27 Jan, 2024 Reviewers invited by journal 27 Jan, 2024 Submission checks completed at journal 23 Jan, 2024 Editor assigned by journal 23 Jan, 2024 First submitted to journal 21 Jan, 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. 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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-3885225","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268786925,"identity":"464376f8-9648-48e4-bfd7-12f7add41f19","order_by":0,"name":"Ali Amiri","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYDACdsYGBgYDBh4GZuYDDCA2YcAM18KWQKwWOIvHgDgt/M3MjZ9uFNyT4W/n+Sbxc4eNHAP74aMb8GmROMzYLJ1jUMwjcZh3m2TvmTRjBp60tBt4rTnM2ADUksDDANQiwdt2OLFBgscMrxZ5oC2/QVrkD/M8k/xLjBaDw4xtYFsMDvOwSRNliyFQizVIi+FhNmNr2bY0YzZCfpE73v74ds6fBHu584cf3nzbZiPHz374GH7vIwEWCRDJRqxyEGD+QIrqUTAKRsEoGDkAAMxhQ/djs+c4AAAAAElFTkSuQmCC","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Ali","middleName":"","lastName":"Amiri","suffix":""},{"id":268786926,"identity":"401d66e6-5bc7-4d5d-bbac-cdc051cb9124","order_by":1,"name":"Bahram Kimiaghalam","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Bahram","middleName":"","lastName":"Kimiaghalam","suffix":""}],"badges":[],"createdAt":"2024-01-21 16:29:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3885225/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3885225/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11760-024-03182-5","type":"published","date":"2024-06-03T12:41:14+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59024249,"identity":"cecc60fd-55c9-40dc-9afe-a85b8d793f68","added_by":"auto","created_at":"2024-06-25 12:41:19","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1001599,"visible":true,"origin":"","legend":"","description":"","filename":"mainarticale.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3885225/v1_covered_7ba135f1-631d-4cdf-95d0-2ca5fd843f7b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Robust Watermarking with PSO and DnCNN","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":"signal-image-and-video-processing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sivp","sideBox":"Learn more about [Signal, Image and Video Processing](http://link.springer.com/journal/11760)","snPcode":"11760","submissionUrl":"https://submission.nature.com/new-submission/11760/3","title":"Signal, Image and Video Processing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"SVD, False positive, Contourlet, PSO, DnCNN","lastPublishedDoi":"10.21203/rs.3.rs-3885225/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3885225/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe NC value obtained for our scheme is very good against jpeg attacks and the results are much better than the compared articles. 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