Unified method for image reconstruction and super-resolution of SFA video sequences

Unified method for image reconstruction and super-resolution of SFA video sequences | 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 Unified method for image reconstruction and super-resolution of SFA video sequences Abdelhamid FSIAN, Jean-Baptiste Thomas, Jon Yngve Hardeberg, Pierre Gouton This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6611052/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Spectral filter array (SFA) cameras provide a cost-effective, single-shot solution for spectral imaging across multiple bands. However, due to the inherent nature of the technology, SFA cameras typically exhibit lower spatial resolution compared to traditional color cameras, and the sparse spatial sampling rate makes demosaicking a challenging task. Existing methods either process frames independently, leading to aliasing artifacts, or apply sequential demosaicking and super-resolution, which fails to fully exploit the temporal redundancy available in multi-frame sequences. In this paper, we propose a novel joint multi-frame demosaicking and super-resolution framework based on deep convolutional networks. Unlike prior work, our approach simultaneously reconstructs high-resolution spectral images while leveraging temporal redundancy from adjacent frames, significantly reducing aliasing artifacts and improving spectral fidelity. Through extensive experimentation on large synthetic spectral video datasets, Our method achieves a PSNR of 32.17 dB, outperforming the best competitor (29.83 dB), with enhanced visual quality. We further validate our approach on real SFA data captured with the CMS-C camera (Silios Technologies), demonstrating its practical applicability and robustness in real-world scenarios. The codes and datasets are available at github.com/HamidFsian/MultiFrameDemoSR Spectral Imaging Demosaicking super-resolution SFA Camera. Full Text Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 19 Nov, 2025 Reviewers agreed at journal 02 Oct, 2025 Reviewers invited by journal 02 Oct, 2025 Editor assigned by journal 11 May, 2025 First submitted to journal 08 May, 2025 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-6611052","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":523989368,"identity":"577a40aa-bcae-4341-bea9-0b1c67104e17","order_by":0,"name":"Abdelhamid FSIAN","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0006-5388-7428","institution":"Université de Bourgogne: Universite de Bourgogne","correspondingAuthor":true,"prefix":"","firstName":"Abdelhamid","middleName":"","lastName":"FSIAN","suffix":""},{"id":523989369,"identity":"a245b88a-5447-430f-ada3-0e81eadc9cf3","order_by":1,"name":"Jean-Baptiste Thomas","email":"","orcid":"","institution":"Université de Bourgogne: Universite de Bourgogne","correspondingAuthor":false,"prefix":"","firstName":"Jean-Baptiste","middleName":"","lastName":"Thomas","suffix":""},{"id":523989370,"identity":"bf827b35-1134-40ec-91cd-5f813096aa5b","order_by":2,"name":"Jon Yngve Hardeberg","email":"","orcid":"","institution":"Norwegian University of Science and Technology - Gjovik Campus: Norges teknisk-naturvitenskapelige universitet i Gjovik","correspondingAuthor":false,"prefix":"","firstName":"Jon","middleName":"Yngve","lastName":"Hardeberg","suffix":""},{"id":523989371,"identity":"d43acf18-f876-4819-a4fa-35fee7c8cdab","order_by":3,"name":"Pierre Gouton","email":"","orcid":"","institution":"Université de Bourgogne: Universite de Bourgogne","correspondingAuthor":false,"prefix":"","firstName":"Pierre","middleName":"","lastName":"Gouton","suffix":""}],"badges":[],"createdAt":"2025-05-07 10:27:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6611052/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6611052/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":93619138,"identity":"d5e9e0a6-854c-491a-8b03-6b69ce760da8","added_by":"auto","created_at":"2025-10-15 17:33:18","extension":"xml","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8503,"visible":true,"origin":"","legend":"","description":"","filename":"jivpJIVPD2500106.xml","url":"https://assets-eu.researchsquare.com/files/rs-6611052/v1/a7574e288d01132b72b7a9c6.xml"},{"id":93619139,"identity":"934f8983-2e26-4cd7-9a97-c19d8376652b","added_by":"auto","created_at":"2025-10-15 17:33:18","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":924,"visible":true,"origin":"","legend":"","description":"","filename":"JIVPD25001065242.go.xml","url":"https://assets-eu.researchsquare.com/files/rs-6611052/v1/627c8ffa7d7c7d1754702023.xml"},{"id":93619140,"identity":"7cd193da-0812-4e3c-b517-d129298e9487","added_by":"auto","created_at":"2025-10-15 17:33:18","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":898,"visible":true,"origin":"","legend":"","description":"","filename":"JIVPD2500106Import.xml","url":"https://assets-eu.researchsquare.com/files/rs-6611052/v1/eff793766b8ff7fd791e4d0f.xml"},{"id":93619931,"identity":"c9ebcb13-c93e-4385-9ff1-f64a081896a3","added_by":"auto","created_at":"2025-10-15 17:41:22","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2566879,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6611052/v1_covered_e9cb1e14-3ea8-4d71-a875-ed00d3cf67ff.pdf"}],"financialInterests":"","formattedTitle":"Unified method for image reconstruction and super-resolution of SFA video sequences","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":true,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"eurasip-journal-on-image-and-video-processing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jivp","sideBox":"Learn more about [EURASIP Journal on Image and Video Processing](http://jivp-eurasipjournals.springeropen.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jivp/default.aspx","title":"EURASIP Journal on Image and Video Processing","twitterHandle":"@SpringerEng","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Spectral Imaging, Demosaicking, super-resolution, SFA Camera.","lastPublishedDoi":"10.21203/rs.3.rs-6611052/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6611052/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Spectral filter array (SFA) cameras provide a cost-effective, single-shot solution for spectral imaging across multiple bands. However, due to the inherent nature of the technology, SFA cameras typically exhibit lower spatial resolution compared to traditional color cameras, and the sparse spatial sampling rate makes demosaicking a challenging task. Existing methods either process frames independently, leading to aliasing artifacts, or apply sequential demosaicking and super-resolution, which fails to fully exploit the temporal redundancy available in multi-frame sequences. In this paper, we propose a novel joint multi-frame demosaicking and super-resolution framework based on deep convolutional networks. Unlike prior work, our approach simultaneously reconstructs high-resolution spectral images while leveraging temporal redundancy from adjacent frames, significantly reducing aliasing artifacts and improving spectral fidelity. Through extensive experimentation on large synthetic spectral video datasets, Our method achieves a PSNR of 32.17 dB, outperforming the best competitor (29.83 dB), with enhanced visual quality. We further validate our approach on real SFA data captured with the CMS-C camera (Silios Technologies), demonstrating its practical applicability and robustness in real-world scenarios. The codes and datasets are available at github.com/HamidFsian/MultiFrameDemoSR","manuscriptTitle":"Unified method for image reconstruction and super-resolution of SFA video sequences","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-15 17:33:14","doi":"10.21203/rs.3.rs-6611052/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2025-11-19T18:15:25+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-10-03T01:51:19+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-02T23:57:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-11T18:15:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"EURASIP Journal on Image and Video Processing","date":"2025-05-08T09:19:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"eurasip-journal-on-image-and-video-processing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jivp","sideBox":"Learn more about [EURASIP Journal on Image and Video Processing](http://jivp-eurasipjournals.springeropen.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jivp/default.aspx","title":"EURASIP Journal on Image and Video Processing","twitterHandle":"@SpringerEng","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"10e60f13-03d2-4e8e-93ae-3ec3feaef19c","owner":[],"postedDate":"October 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T17:09:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-15 17:33:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6611052","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6611052","identity":"rs-6611052","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}