Underwater image restoration has been a challenging problem for decades since the advent of underwater photography. Most solutions focus on shallow water scenarios, where the scene is uniformly illuminated by the sunlight. However, the vast majority of uncharted underwater terrain is located beyond 200 meters depth where natural light is scarce and artificial illumination is needed. In such cases, light sources co-moving with the camera, dynamically change the scene appearance, which make shallow water restoration methods inadequate. In particular for multi-light source systems (composed of dozens of LEDs nowadays), calibrating each light is time-consuming, error-prone and tedious, and we observe that only the integrated illumination within the viewing volume of the camera is critical, rather than the individual light sources. The key idea of this paper is therefore to exploit the appearance changes of objects or the seafloor, when traversing the viewing frustum of the camera. Through new constraints assuming Lambertian surfaces, corresponding image pixels constrain the light field in front of the camera, and for each voxel a signal factor and a backscatter value are stored in a volumetric grid that can be used for very efficient image restoration of camera-light platforms, which facilitates consistently texturing large 3D models and maps that would otherwise be dominated by lighting and medium artifacts. To validate the effectiveness of our approach, we conducted extensive experiments on simulated and real-world datasets. The results of these experiments demonstrate the robustness of our approach in restoring the true albedo of objects, while mitigating the influence of lighting and medium effects. Furthermore, we demonstrate our approach can be readily extended to other scenarios, including in-air imaging with artificial illumination or other similar cases.

翻译：水下图像恢复自水下摄影问世以来一直是一个具有挑战性的问题。大多数解决方案聚焦于浅水场景，其中场景被太阳光均匀照亮。然而，绝大部分未被勘测的水下地形位于200米深度以下，该区域自然光稀缺，需要人工照明。在此类情况下，与相机同步移动的光源会动态改变场景外观，导致浅水恢复方法失效。特别对于由数十个LED组成的多光源系统而言，标定每个光源耗时、易错且繁琐。我们观察到，真正关键的是相机视域范围内的集成照明，而非单个光源。因此，本文的核心思想是利用物体或海床在穿越相机视锥时外观变化。通过假设朗伯表面引入新约束，对应图像像素约束相机前方的光场，并在体素网格中存储每个体素的信号因子和后向散射值。该网格可用于实现极高效的相机-光平台图像恢复，从而支持大规模3D模型与地图的一致性纹理贴图——否则这些模型与地图将被照明和介质伪影主导。为验证方法有效性，我们在仿真和真实数据集上开展广泛实验。结果表明，该方法在恢复物体真实反射率的同时，能有效抑制照明和介质效应的影响。进一步地，我们证明该方法可轻松拓展至其他场景，包括人工照明下的空气中成像或其他类似情况。