Global strategy for robust air‐light estimation in dehazing

Author:

Zhu Zhu12,Zhang Xiaoguo2ORCID

Affiliation:

1. School of Computer Engineering Jinling Institute of Technology Nanjing China

2. School of Instrument Science and Engineering Southeast University Nanjing China

Abstract

AbstractThis 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.

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

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