Optimising Hazy Image Clarity Through Blue Channel Balancing in Lab Color Space

Optimising Hazy Image Clarity Through Blue Channel Balancing in Lab Color Space | 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 Optimising Hazy Image Clarity Through Blue Channel Balancing in Lab Color Space Ibrahim Salim Sulaiman Farsi, Mohd Rahim, Falah Y H Ahmed, Devi Willieam Anggara1, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7618067/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Feb, 2026 Read the published version in Discover Artificial Intelligence → Version 1 posted 13 You are reading this latest preprint version Abstract The presence of haze in the atmosphere results in a bluish and yellowish tint in the affected area. This research assessed the histogram of hazy images and found that the blue channel was overly dominant, particularly in images exhibiting non-homogeneous haze. This pronounced blue channel is associated with the blue or yellow appearance of the haze, especially in the sky regions of the images. The blue channel in the haze image causes a loss of details and visual distraction. To address this issue, this research proposed a blue channel balancing method within the LAB colour space. This adjustment reduces the excessive blue levels, thereby enhancing image clarity by mitigating the hazy effect. Qualitative results indicate that balancing the blue channel significantly improves the dehazing process, making it more effective in removing haze, even in conditions where the haze is quite dense. However, it is important to note that this method may result in a slight darkening of the image and the appearance of twinkles (i.e., sparkles or localised brightening in certain areas of the image). The blue channel balancing method has proven particularly effective under medium and low haze conditions. Similarly, this method effectively reduces haze in images that are heavily affected by haze. Dehazing Haze Thickness Image Enhancement Image Processing Computer Vision Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 09 Feb, 2026 Read the published version in Discover Artificial Intelligence → Version 1 posted Editorial decision: Revision requested 05 Nov, 2025 Reviews received at journal 03 Nov, 2025 Reviews received at journal 02 Nov, 2025 Reviews received at journal 01 Nov, 2025 Reviews received at journal 20 Oct, 2025 Reviewers agreed at journal 14 Oct, 2025 Reviewers agreed at journal 12 Oct, 2025 Reviewers agreed at journal 08 Oct, 2025 Reviewers agreed at journal 08 Oct, 2025 Reviewers invited by journal 07 Oct, 2025 Editor assigned by journal 19 Sep, 2025 Submission checks completed at journal 19 Sep, 2025 First submitted to journal 15 Sep, 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. 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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-7618067","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":531142798,"identity":"ee2bbec1-763f-4ddd-ab22-2d424315afb9","order_by":0,"name":"Ibrahim Salim Sulaiman 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