Wang Quan, Cai Chengtao, Zhang Weidong, Li Peitong, Xin Boyu
Appl Opt. 2022 Feb 20;61(6):C46-C54. doi: 10.1364/AO.433558.
Underwater images have different color casts due to different attenuation conditions, such as bluish, greenish, and yellowish. In addition, due to floating particles and special illumination, underwater images have problems such as the lack of detail and unnecessary noise. To handle the above problems, this paper proposes a new, to the best of our knowledge, three-step adaptive enhancement method. For the first step, adaptive color correction, the three channels are adjusted based on the intermediate color channel, which is calculated by considering the positional relationship of the histogram distribution. For the second step, denoise and restore details, we first transform the space to hue, saturation, value (HSV), a detailed restoration method based on the edge-preserving decomposition that restores the lost detail while removing the influence of some noise. For the third step, we improve the global contrast. Still in the HSV space, a simple linear stretch strategy is applied to the saturation channel. Experiments on the standard underwater image enhancement benchmark data set have proved that our method yields more natural colors and more valuable detailed information than several state-of-the-art methods. In addition, our method also improves the visibility of underwater images captured by low-light scenes and different hardware cameras.
由于不同的衰减条件，水下图像会有不同的色偏，比如偏蓝、偏绿和偏黄。此外，由于漂浮颗粒和特殊光照，水下图像存在细节缺失和不必要噪声等问题。为了解决上述问题，据我们所知，本文提出了一种新的三步自适应增强方法。第一步是自适应色彩校正，基于中间颜色通道对三个通道进行调整，该中间颜色通道是通过考虑直方图分布的位置关系计算得出的。第二步是去噪和恢复细节，我们首先将空间转换为色相、饱和度、明度（HSV），基于保边分解的详细恢复方法在去除一些噪声影响的同时恢复丢失的细节。第三步，我们提高全局对比度。同样在HSV空间中，对饱和度通道应用简单的线性拉伸策略。在标准水下图像增强基准数据集上的实验证明，与几种最先进的方法相比，我们的方法能产生更自然的颜色和更有价值的详细信息。此外，我们的方法还提高了在低光照场景和不同硬件相机拍摄的水下图像的可视性。
