Blind Image Deblurring: When Patch-wise Minimal Pixels Prior Meets Fractional-Order Method

Blind Image Deblurring: When Patch-wise Minimal Pixels Prior Meets Fractional-Order Method | 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 Blind Image Deblurring: When Patch-wise Minimal Pixels Prior Meets Fractional-Order Method Tingting Wu, Shaojie Wan, Chenchen Feng, Hao Zhang, Tieyong Zeng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4469860/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Dec, 2024 Read the published version in Journal of Mathematical Imaging and Vision → Version 1 posted 9 You are reading this latest preprint version Abstract Blind image deblurring is a challenging issue in image processing. In blind image deblurring, the typical approach involves iteratively estimating both the blur kernel and latent image until convergence to the blur kernel of the observed image is achieved. Recently, several approaches have been attempted to develop a sophisticated regularization to obtain the clean image. However, existing methods often struggle to effectively handle ringing artifacts and local blur. To overcome these limitations, we introduce a fractional-order variational model. This model alleviates the ringing artifacts through the selection of an optimal derivative. Subsequently, to refine the latent image further, we leverage the local prior, namely Patch-wise Minimal Pixels (PMP) prior. Since the PMP prior of clean image blocks is much sparser than that of blurred ones, it is capable of discriminating between clean and blurred image blocks. We illustrate the effective integration of the fractional-order operations and the PMP prior within our proposed approach. Moreover, the convergence of our algorithm has been proven as the values of the objective function monotonically decrease. Extensive experiments on different datasets demonstrate the superiority of the proposed method compared with other methods in terms of reconstruction quality for blind deblurring. Image deblurring Blind deblurring Fractional-order Ringing artifacts Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 30 Dec, 2024 Read the published version in Journal of Mathematical Imaging and Vision → Version 1 posted Editorial decision: Revision requested 18 Sep, 2024 Reviews received at journal 10 Sep, 2024 Reviews received at journal 09 Sep, 2024 Reviewers agreed at journal 13 Jul, 2024 Reviewers agreed at journal 13 Jul, 2024 Reviewers invited by journal 05 Jun, 2024 Editor assigned by journal 29 May, 2024 Submission checks completed at journal 29 May, 2024 First submitted to journal 23 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-4469860","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":312756149,"identity":"be19750c-e325-4693-80c2-8cca99eca9a7","order_by":0,"name":"Tingting Wu","email":"","orcid":"","institution":"Nanjing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"Tingting","middleName":"","lastName":"Wu","suffix":""},{"id":312756150,"identity":"3c4c2f1d-d188-4390-9847-b533cd8b571a","order_by":1,"name":"Shaojie Wan","email":"","orcid":"","institution":"Nanjing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"Shaojie","middleName":"","lastName":"Wan","suffix":""},{"id":312756151,"identity":"f694b1dd-24c2-4b07-8b63-ba2a6f8ee284","order_by":2,"name":"Chenchen Feng","email":"","orcid":"","institution":"Nanjing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"Chenchen","middleName":"","lastName":"Feng","suffix":""},{"id":312756153,"identity":"20be22b6-0df0-4a70-911a-abc4bac0a686","order_by":3,"name":"Hao Zhang","email":"","orcid":"","institution":"Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Zhang","suffix":""},{"id":312756154,"identity":"50eac1b3-57d3-4100-aae7-f2711be17b3e","order_by":4,"name":"Tieyong Zeng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYLCCD0BsAMTMDAeA5AEGNsYGAjoYZzAwSJCmhZmHJC3y7b2HX9vm2NWZMzA/ky44wyDHdyOB7eEMfI7qOZdmnbstWcKygc1MesYNBmPJGwnshhvwOUoix8w4dxuzhMEBHjZpng8MiRuAtkg+wKOFTf6NmbHltnq4lnqCWngkeIwfM247DNVygyHBAKQFn8MkeHLMGHu3HZfccJjN2JrnjIThzDMP2yTxeV++/Yzxh5/bqvkNjjc/vM1zzEae73jyMckePFpA3pEAU8wQW4GYYEQyMH8gpGIUjIJRMApGOAAAiyxJC0YIVZwAAAAASUVORK5CYII=","orcid":"","institution":"Chinese University of Hong Kong","correspondingAuthor":true,"prefix":"","firstName":"Tieyong","middleName":"","lastName":"Zeng","suffix":""}],"badges":[],"createdAt":"2024-05-24 04:08:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4469860/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4469860/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10851-024-01221-x","type":"published","date":"2024-12-30T15:57:14+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":73093283,"identity":"3d16c0c0-1ef6-4251-8596-6900d38d07b5","added_by":"auto","created_at":"2025-01-06 16:12:47","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9387974,"visible":true,"origin":"","legend":"","description":"","filename":"LATEX.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4469860/v1_covered_ba971fb9-036d-4f5a-9cd1-92efa0b3612d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Blind Image Deblurring: When Patch-wise Minimal Pixels Prior Meets Fractional-Order Method","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":"journal-of-mathematical-imaging-and-vision","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jmiv","sideBox":"Learn more about [Journal of Mathematical Imaging and Vision](http://link.springer.com/journal/10851)","snPcode":"10851","submissionUrl":"https://submission.nature.com/new-submission/10851/3","title":"Journal of Mathematical Imaging and Vision","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Image deblurring, Blind deblurring, Fractional-order, Ringing artifacts","lastPublishedDoi":"10.21203/rs.3.rs-4469860/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4469860/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Blind image deblurring is a challenging issue in image processing. 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