3D Rainy Stereoscopic Video Stabilization Using Depth Estimation

3D Rainy Stereoscopic Video Stabilization Using Depth Estimation | 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 3D Rainy Stereoscopic Video Stabilization Using Depth Estimation R Mehala, K. Mahesh, Eswaran Perumal This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7082910/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The process of enhancing the video’s quality by removing unwanted effects of camera shakes and jitters is called Video Stabilization (VS). However, the 3-Dimensional (3D) rainy stereoscopic VS process was not concentrated on any of the prevailing research work. Therefore, in this framework, an effective 3D rainy stereoscopic VS with depth estimation and Shape Autotuning Liebovitch map Cheetah Chase Algorithm with Convolution Neural Network (SA-LmCCA-CNN) is proposed. Primarily, the input videos are converted into a number of frames. After that, by using Pairnorm L0 Gradient Minimization (Pn-LGM), the raindrops in each frame are removed. Later, the overlapping region and depth estimation are processed, and by using the Liebovitch map Cheetah Chase Algorithm (LmCCA), the energy function is diminished. Likewise, to mitigate the hallucination issue, a mesh is generated by utilizing Alternating Least Squares-Locally Constrained Representations (ALS-LCR). Then, from the hallucination-mitigated image and energy function minimized image, the feature points are extracted. Later, by employing SA-LmCCA-CNN, the stable and unstable frames are classified. If the frame is unstable, then the frame undergoes motion and camera path corrections, followed by raindrop reconstruction; otherwise, raindrop reconstruction is done directly for a stable frame. Lastly, in order to get the stabilized video, the frames are synthesized. The experimental analysis proved the proposed model’s robustness in 3D rainy stereoscopic VS by attaining a stability score of 0.93. Video stabilization 3D rainy stereoscopic video Depth estimation Hallucination mitigation Texture mapping Lucas Kanade-Triparametric correlation coefficient (LKT) and Low-Pass Filtering (LPF) Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-7082910","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":484763958,"identity":"0ea4137c-096f-4f5a-bf0d-86bade1b71e4","order_by":0,"name":"R Mehala","email":"data:image/png;base64,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","orcid":"","institution":"ALAGAPPA UNIVERSITY, KARAIKUDI","correspondingAuthor":true,"prefix":"","firstName":"R","middleName":"","lastName":"Mehala","suffix":""},{"id":484763959,"identity":"82cfc5f0-b87f-4e80-9ea6-392ae2fc13df","order_by":1,"name":"K. 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However, the 3-Dimensional (3D) rainy stereoscopic VS process was not concentrated on any of the prevailing research work. Therefore, in this framework, an effective 3D rainy stereoscopic VS with depth estimation and Shape Autotuning Liebovitch map Cheetah Chase Algorithm with Convolution Neural Network (SA-LmCCA-CNN) is proposed. Primarily, the input videos are converted into a number of frames. After that, by using Pairnorm L0 Gradient Minimization (Pn-LGM), the raindrops in each frame are removed. Later, the overlapping region and depth estimation are processed, and by using the Liebovitch map Cheetah Chase Algorithm (LmCCA), the energy function is diminished. Likewise, to mitigate the hallucination issue, a mesh is generated by utilizing Alternating Least Squares-Locally Constrained Representations (ALS-LCR). Then, from the hallucination-mitigated image and energy function minimized image, the feature points are extracted. Later, by employing SA-LmCCA-CNN, the stable and unstable frames are classified. If the frame is unstable, then the frame undergoes motion and camera path corrections, followed by raindrop reconstruction; otherwise, raindrop reconstruction is done directly for a stable frame. Lastly, in order to get the stabilized video, the frames are synthesized. The experimental analysis proved the proposed model\u0026rsquo;s robustness in 3D rainy stereoscopic VS by attaining a stability score of 0.93.\u003c/p\u003e","manuscriptTitle":"3D Rainy Stereoscopic Video Stabilization Using Depth Estimation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-16 06:17:29","doi":"10.21203/rs.3.rs-7082910/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fdce9d59-62e6-46cc-8e79-b1f60faf7c1f","owner":[],"postedDate":"July 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-06T02:23:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-16 06:17:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7082910","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7082910","identity":"rs-7082910","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}