Residual Channel Prior-Guided Multi-Scale Progressive Dehazing Network with Hybrid Attention

Residual Channel Prior-Guided Multi-Scale Progressive Dehazing Network with Hybrid Attention | 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 Residual Channel Prior-Guided Multi-Scale Progressive Dehazing Network with Hybrid Attention Yiming Xing, Jindong Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5336092/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Mar, 2025 Read the published version in Multimedia Systems → Version 1 posted 9 You are reading this latest preprint version Abstract Haze significantly degrades image quality, impacting tasks such as object detection and semantic segmentation. Existing dehazing methods often perform well on synthetic images but struggle with real-world hazy images, particularly those with non-uniform haze distribution. To address this challenge, we propose a Residual Channel Prior-Guided Multi-Scale Progressive Dehazing Network (MPDNet). MPDNet leverages the rich structural information contained in the Residual Channel Prior (RCP) of hazy images and introduces a Prior-Guided Block (PGB) to extract RCP maps at different dehazing stages. To better apply prior knowledge at different stages, we designed a progressive dehazing network. An Attention-Guided Feature Memory module (AFM) is designed to explore the correlation between current input and historical information, enabling feature transfer across stages. Additionally, a Multi-Scale Dehazing Unit (MDU) incorporating a Multi-Scale Feature Extraction Module (MSFEM) with a hybrid attention mechanism is utilized to restore haze-free images. Extensive experiments demonstrate that MPDNet achieves state-of-the-art performance on both synthetic and real datasets, particularly excelling in handling non-uniform hazy images. Image Dehazing Multi-Scale Image Prior Hybrid Attention Dilated Convolution Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 16 Mar, 2025 Read the published version in Multimedia Systems → Version 1 posted Editorial decision: Revision requested 29 Dec, 2024 Reviews received at journal 26 Dec, 2024 Reviews received at journal 23 Dec, 2024 Reviewers agreed at journal 09 Dec, 2024 Reviewers agreed at journal 09 Dec, 2024 Reviewers invited by journal 09 Dec, 2024 Editor assigned by journal 07 Dec, 2024 Submission checks completed at journal 26 Oct, 2024 First submitted to journal 26 Oct, 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-5336092","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":370703579,"identity":"dc4d246d-e767-49e7-9dbb-7bab9c9b979c","order_by":0,"name":"Yiming Xing","email":"","orcid":"","institution":"Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Yiming","middleName":"","lastName":"Xing","suffix":""},{"id":370703580,"identity":"4068f4de-209e-47f6-b122-636e7e313171","order_by":1,"name":"Jindong Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYDACCRDBAyQPgBgGEjz8zMyHH5CgpcBGTrKdLc2AsBYQAGv5kGZscJ5HQQKnciCQn9387OEXGYs8vuO9h18wGBxO3HyYh8GAocYmGpcWxjnHzI1leCSKJc+cS7MAadl2mPfAA4ZjabkNOLQwSySYSUvwSCRuuJFjZgDRwpdgwNhwGKcWNon0b6haNjfzGEjg08IjkWMm+QGixfgBgwHQ+8wEtEhI5JRJAzUmzjxzxgwYLzZyEoeBgZyAxy/yM9K3Sf7sqUvsO95j/IHhDzAq+w8ffvChxganFnAQ8PZA/CX9ByaUgEc5CDD++AHR+oGAwlEwCkbBKBihAAB2BVhoIEfKBgAAAABJRU5ErkJggg==","orcid":"","institution":"Jilin University","correspondingAuthor":true,"prefix":"","firstName":"Jindong","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-10-26 07:23:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5336092/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5336092/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00530-025-01754-0","type":"published","date":"2025-03-16T15:57:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":78689843,"identity":"e6bfa69c-658b-46e0-b735-bb5d3e259cdc","added_by":"auto","created_at":"2025-03-17 16:13:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1977467,"visible":true,"origin":"","legend":"","description":"","filename":"ResidualChannelPriorGuidedMultiScaleProgressiveDehazingNetworkwithHybridAttention.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5336092/v1_covered_6d71f03b-a1d6-4e9a-865d-1fbc62ee5380.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Residual Channel Prior-Guided Multi-Scale Progressive Dehazing Network with Hybrid Attention","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":"multimedia-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mmsj","sideBox":"Learn more about [Multimedia Systems](http://link.springer.com/journal/530)","snPcode":"530","submissionUrl":"https://submission.nature.com/new-submission/530/3","title":"Multimedia Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Image Dehazing, Multi-Scale, Image Prior, Hybrid Attention, Dilated Convolution","lastPublishedDoi":"10.21203/rs.3.rs-5336092/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5336092/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHaze significantly degrades image quality, impacting tasks such as object detection and semantic segmentation. 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