Zhang Jiening, Yu Qing, Hou Guojia
Appl Opt. 2024 Apr 1;63(10):2728-2736. doi: 10.1364/AO.514749.
Due to the absorbing and scattering effects, underwater images are often degraded by low contrast, color cast, and haze, which have limited their further applications to underwater vision task. To address this issue, we propose a hybrid framework by adaptive color correction and dehazing for underwater image restoration. Specifically, according to the color attenuation principle, we first design an adaptive color compensation strategy to correct the color cast of the underwater image. In addition, based on an underwater image formation model, we develop a robust dehazing algorithm, in which a new scoring formula across three indicators (i.e., darkness, distance, and blurriness) and a double-max DCP method are proposed to estimate the background light and transmission map, respectively. The experimental results validate that the proposed method is effective in color correction and dehazing. Both qualitative and quantitative comparisons further demonstrate that the proposed method outperforms several state-of-the-art methods.
由于吸收和散射效应，水下图像常常因对比度低、偏色和雾霾而退化，这限制了它们在水下视觉任务中的进一步应用。为了解决这个问题，我们提出了一种用于水下图像恢复的自适应色彩校正和去雾混合框架。具体来说，根据颜色衰减原理，我们首先设计了一种自适应色彩补偿策略来校正水下图像的偏色。此外，基于水下图像形成模型，我们开发了一种鲁棒的去雾算法，其中提出了一种跨三个指标（即暗度、距离和模糊度）的新评分公式和一种双最大值暗通道先验（DCP）方法，分别用于估计背景光和透射率图。实验结果验证了所提方法在色彩校正和去雾方面是有效的。定性和定量比较进一步表明，所提方法优于几种现有最先进的方法。
