To enhance the reliability of airport surveillance systems during heavy fog, this paper proposes a method to estimate atmospheric light values for airport images dehazing. First, the method estimates the atmospheric transmittance based on the dark channel prior (DCP) and applies a standard atmospheric scattering model to restore the initial dehazed image. Second, the clarity coefficient is introduced to provide feedback on the dehazed image. Based on this feedback, a rule is designed to iteratively update the atmospheric light value, adjusting it until the clarity coefficient peaks. Finally, guided by the updated atmospheric light value, the atmospheric scattering model reconstructs the optimal fog-free image. Experimental results demonstrate that, compared with traditional DCP method, the proposed method achieves more accurate atmospheric light values, resulting in more natural dehazing and outperforming existing objective evaluation indices for image dehazing