Image Dehazing Algorithm Based on Light-Value Weighted Allocation and Multi-Layer Restricted Perception

Image Dehazing Algorithm Based on Light-Value Weighted Allocation and Multi-Layer Restricted Perception | 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 Article Image Dehazing Algorithm Based on Light-Value Weighted Allocation and Multi-Layer Restricted Perception Dong yang Shi, Sheng Huang, Wei Zhao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6133676/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted 8 You are reading this latest preprint version Abstract Background In image dehazing, the dehazing performance in bright regions and the model's robustness to noise are critical evaluation criteria. However, existing dehazing models often suffer from distortions in the bright areas and exhibit weak noise resistance. We propose an image dehazing algorithm based on light-value weighted allocation and multi-layer restricted perception (DWARP) to address these issues. Methods The proposed algorithm first constructs an atmospheric light estimation module based on weighted allocation. It reduces the initial estimation error by zeroing out overexposed pixel values, then identifying key factors affecting atmospheric light estimation and assigning weights accordingly. Finally, a threshold-restricted adjustment is applied to the estimated result, achieving a three-stage refinement in atmospheric light estimation accuracy. Secondly, by computing the universal range of transmittance for both bright and non-bright regions, a multi-layer restricted perception scheme for transmittance is designed. This approach transforms the distortion issue in bright regions into a problem of reducing transmittance estimation errors. Finally, to enhance the visual quality of the dehazed image and improve the model's noise robustness, a brightness adjustment module and a Gaussian denoising module are embedded into the dehazing model. Results Experimental results demonstrate that the DWARP algorithm effectively prevents distortion in the dehazing process for bright regions and enhances the model’s noise robustness. The DWARP algorithm achieved an average PSNR of 37.41 dB, an average SSIM of 88.74%, and an average VIF of 0.89 across four datasets, with an average dehazing time of 0.633 seconds. Compared to the RIDCP algorithm, DWARP improved the PSNR by an average of 6.63 dB, SSIM by 2.18%, and VIF by 0.03 while enhancing dehazing efficiency by an average of 0.055 seconds. Conclusion To validate the effectiveness of the DWARP algorithm, we conducted dehazing experiments on four foggy datasets, demonstrating the proposed algorithm's effectiveness and superiority. The DWARP algorithm not only effectively processes bright regions, such as the sky, in foggy images but also exhibits strong noise resistance, validating the scientific and theoretical correctness of the proposed improvements. This dehazing model provides a novel approach for fog removal in fields such as intelligent transportation, contributing to the advancement and development of these areas. Physical sciences/Mathematics and computing/Computer science Physical sciences/Mathematics and computing/Information technology Physical sciences/Mathematics and computing/Software Physical sciences/Mathematics and computing/Computational science Physical sciences/Mathematics and computing/Scientific data Image dehazing Bright regions Noise resistance Weighted allocation Restricted perception Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 11 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Accepted 06 Apr, 2025 Reviews received at journal 02 Apr, 2025 Reviews received at journal 01 Apr, 2025 Reviewers agreed at journal 01 Apr, 2025 Reviewers agreed at journal 01 Apr, 2025 Reviewers invited by journal 01 Apr, 2025 Submission checks completed at journal 30 Mar, 2025 First submitted to journal 29 Mar, 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. 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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-6133676","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":437552083,"identity":"564cfac9-6bc4-4ac8-b136-b61a224c5c40","order_by":0,"name":"Dong yang Shi","email":"","orcid":"","institution":"School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"Dong","middleName":"yang","lastName":"Shi","suffix":""},{"id":437552084,"identity":"d2b55b27-0d50-4491-92b6-b40c6af35d71","order_by":1,"name":"Sheng Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYBACef7G5sc/Ktjk7NubDxCnxXDG4TZjhjN8xgY8xxKItOZAeoM0Y5tc4gaJHAPidDA2HGwwLmwzMzaXyPl44w2DnZxuAwEt7MyNDY9nnEuTs+x5u9lyDkOysdkBImwx4Ck7ZsxwPHebNA/DgcRthLQA1TRI8LD9T2w4kPOMeC3SPG1siRtO5LARp8VwxsE2wxln2Iwle44ZW84xIMIv8vztjx98AEYlP3vzwxtvKuzkCGpBARI8REYNshZSdYyCUTAKRsGIAACwlUh9kYelXQAAAABJRU5ErkJggg==","orcid":"","institution":"School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications","correspondingAuthor":true,"prefix":"","firstName":"Sheng","middleName":"","lastName":"Huang","suffix":""},{"id":437552085,"identity":"ca5b7712-3865-4255-ac5c-07225e62d90d","order_by":2,"name":"Wei Zhao","email":"","orcid":"","institution":"School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zhao","suffix":""}],"badges":[],"createdAt":"2025-03-01 09:08:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6133676/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6133676/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-97567-2","type":"published","date":"2025-04-11T16:05:54+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80558742,"identity":"bd95a76d-c1c4-4b27-b198-857c4770eb4c","added_by":"auto","created_at":"2025-04-14 16:16:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2529577,"visible":true,"origin":"","legend":"","description":"","filename":"ImageDehazingAlgorithmBasedonLightValueWeightedAllocationandMultiLayerRestrictedPerception.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6133676/v1_covered_8bff18c4-3ce3-4973-b66a-817c5bb75820.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Image Dehazing Algorithm Based on Light-Value Weighted Allocation and Multi-Layer Restricted Perception","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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Image dehazing, Bright regions, Noise resistance, Weighted allocation, Restricted perception","lastPublishedDoi":"10.21203/rs.3.rs-6133676/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6133676/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIn image dehazing, the dehazing performance in bright regions and the model's robustness to noise are critical evaluation criteria. However, existing dehazing models often suffer from distortions in the bright areas and exhibit weak noise resistance. We propose an image dehazing algorithm based on light-value weighted allocation and multi-layer restricted perception (DWARP) to address these issues.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe proposed algorithm first constructs an atmospheric light estimation module based on weighted allocation. It reduces the initial estimation error by zeroing out overexposed pixel values, then identifying key factors affecting atmospheric light estimation and assigning weights accordingly. Finally, a threshold-restricted adjustment is applied to the estimated result, achieving a three-stage refinement in atmospheric light estimation accuracy. Secondly, by computing the universal range of transmittance for both bright and non-bright regions, a multi-layer restricted perception scheme for transmittance is designed. This approach transforms the distortion issue in bright regions into a problem of reducing transmittance estimation errors. Finally, to enhance the visual quality of the dehazed image and improve the model's noise robustness, a brightness adjustment module and a Gaussian denoising module are embedded into the dehazing model.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eExperimental results demonstrate that the DWARP algorithm effectively prevents distortion in the dehazing process for bright regions and enhances the model\u0026rsquo;s noise robustness. The DWARP algorithm achieved an average PSNR of 37.41 dB, an average SSIM of 88.74%, and an average VIF of 0.89 across four datasets, with an average dehazing time of 0.633 seconds. Compared to the RIDCP algorithm, DWARP improved the PSNR by an average of 6.63 dB, SSIM by 2.18%, and VIF by 0.03 while enhancing dehazing efficiency by an average of 0.055 seconds.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eTo validate the effectiveness of the DWARP algorithm, we conducted dehazing experiments on four foggy datasets, demonstrating the proposed algorithm's effectiveness and superiority. The DWARP algorithm not only effectively processes bright regions, such as the sky, in foggy images but also exhibits strong noise resistance, validating the scientific and theoretical correctness of the proposed improvements. This dehazing model provides a novel approach for fog removal in fields such as intelligent transportation, contributing to the advancement and development of these areas.\u003c/p\u003e","manuscriptTitle":"Image Dehazing Algorithm Based on Light-Value Weighted Allocation and Multi-Layer Restricted Perception","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-03 17:44:59","doi":"10.21203/rs.3.rs-6133676/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-04-07T03:18:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-02T16:10:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-02T01:45:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"245153103780433951530127696557947234976","date":"2025-04-02T01:42:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"23627543445059719762226814070536032028","date":"2025-04-02T01:13:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-02T01:10:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-30T11:25:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-29T14:22:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"861b0a6b-0611-4fc7-a25d-a3b4bdf19ace","owner":[],"postedDate":"April 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46591905,"name":"Physical sciences/Mathematics and computing/Computer science"},{"id":46591906,"name":"Physical sciences/Mathematics and computing/Information technology"},{"id":46591907,"name":"Physical sciences/Mathematics and computing/Software"},{"id":46591908,"name":"Physical sciences/Mathematics and computing/Computational science"},{"id":46591909,"name":"Physical sciences/Mathematics and computing/Scientific data"}],"tags":[],"updatedAt":"2025-04-14T16:11:34+00:00","versionOfRecord":{"articleIdentity":"rs-6133676","link":"https://doi.org/10.1038/s41598-025-97567-2","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-04-11 16:05:54","publishedOnDateReadable":"April 11th, 2025"},"versionCreatedAt":"2025-04-03 17:44:59","video":"","vorDoi":"10.1038/s41598-025-97567-2","vorDoiUrl":"https://doi.org/10.1038/s41598-025-97567-2","workflowStages":[]},"version":"v1","identity":"rs-6133676","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6133676","identity":"rs-6133676","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}