稳健性(进化)
计算机科学
像素
人工智能
计算机视觉
集合(抽象数据类型)
算法
生物化学
化学
基因
程序设计语言
摘要
Abstract This letter proposes a novel approach to enhance the robustness of air‐light estimation for dehazing. Unlike most existing methods, it employs a global strategy, considering all pixels instead of specific individual ones, for recovering air‐light. Through an iterative algorithm via the Gray World (GW), the authors extract the air‐light orientation from the entire image. Next, a global detail‐preserving algorithm is designed to determine the optimal magnitude of air‐light. Experimental results on a diverse set of hazy images reveal that the authors’ method outperforms other state‐of‐the‐art alternatives, highlighting the advantage of air‐light estimation using the entire image information.
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