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.
翻译：本文介绍Hazedefy，一种轻量级且面向应用的去雾处理流程，旨在实现实时视频与实时摄像头画面的增强。Hazedefy基于暗通道先验（DCP）概念与大气散射模型，优先考虑计算简洁性与在消费级硬件上的实际可部署性。其关键要素包括：伽马自适应重建、具有数值稳定性下界的快速透射率近似、基于分数顶部像素平均的稳定大气光估计器，以及可选的颜色平衡阶段。该流程适用于移动与嵌入式应用，对真实世界图像与视频的实验演示表明，其可在无需GPU加速的情况下提升可见度与对比度。
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