{"ID":2827589,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.16609","arxiv_id":"2512.16609","title":"Hazedefy: A Lightweight Real-Time Image and Video Dehazing Pipeline for Practical Deployment","abstract":"This paper introduces Hazedefy, a lightweight and application-focused dehazing pipeline intended for real-time video and live camera feed enhancement. Hazedefy prioritizes computational simplicity and practical deployability on consumer-grade hardware, building upon the Dark Channel Prior (DCP) concept and the atmospheric scattering model. Key elements include gamma-adaptive reconstruction, a fast transmission approximation with lower bounds for numerical stability, a stabilized atmospheric light estimator based on fractional top-pixel averaging, and an optional color balance stage. The pipeline is suitable for mobile and embedded applications, as experimental demonstrations on real-world images and videos show improved visibility and contrast without requiring GPU acceleration.","short_abstract":"This paper introduces Hazedefy, a lightweight and application-focused dehazing pipeline intended for real-time video and live camera feed enhancement. Hazedefy prioritizes computational simplicity and practical deployability on consumer-grade hardware, building upon the Dark Channel Prior (DCP) concept and the atmosphe...","url_abs":"https://arxiv.org/abs/2512.16609","url_pdf":"https://arxiv.org/pdf/2512.16609v1","authors":"[\"Ayush Bhavsar\"]","published":"2025-12-18T14:50:35Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}