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.

通过对物体外观变化或海底的利用，利用摄像机视截锥体，新的约束条件假设为兰伯特表面，对应的图像像素约束摄像机前的光场，并且为每个体素存储一个信号因子和后向散射值，该体素网格可用于高效地恢复摄像机光平台的图像，这有助于保持大型 3D 模型和地图的一致纹理，否则这些模型和地图将被光照和介质伪像所主导。在模拟和实际数据集上进行了大量实验以验证我们方法的有效性，实验结果证明了我们方法在恢复物体真实反射率的同时减少了光照和介质效应的影响。此外，我们还展示了我们的方法可以轻松扩展到其他场景，包括带人工照明的空中成像或其他类似情况。