Bi Xiuwen, Wang Pengfei, Wu Tao, Zha Fusheng, Xu Peng
Appl Opt. 2022 Oct 10;61(29):8826-8832. doi: 10.1364/AO.463099.
Absorption and scattering by aqueous media can attenuate light and cause underwater optical imagery difficulty. Artificial light sources are usually used to aid deep-sea imaging. Due to the limited dynamic range of standard cameras, artificial light sources often cause underwater images to be underexposed or overexposed. By contrast, event cameras have a high dynamic range and high temporal resolution but cannot provide frames with rich color characteristics. In this paper, we exploit the complementarity of the two types of cameras to propose an efficient yet simple method for image enhancement of uneven underwater illumination, which can generate enhanced images containing better scene details and colors similar to standard frames. Additionally, we create a dataset recorded by the Dynamic and Active-pixel Vision Sensor that includes both event streams and frames, enabling testing of the proposed method and frame-based image enhancement methods. The experimental results conducted on our dataset with qualitative and quantitative measures demonstrate that the proposed method outperforms the compared enhancement algorithms.
水体介质的吸收和散射会使光线衰减，导致水下光学成像困难。通常使用人工光源来辅助深海成像。由于标准相机的动态范围有限，人工光源常常导致水下图像曝光不足或曝光过度。相比之下，事件相机具有高动态范围和高时间分辨率，但无法提供具有丰富色彩特征的帧。在本文中，我们利用这两种相机的互补性，提出了一种高效且简单的方法来增强不均匀水下光照下的图像，该方法可以生成包含更好场景细节且颜色类似于标准帧的增强图像。此外，我们创建了一个由动态和有源像素视觉传感器记录的数据集，其中包括事件流和帧，从而能够测试所提出的方法以及基于帧的图像增强方法。在我们的数据集上进行的定性和定量实验结果表明，所提出的方法优于比较的增强算法。
