Liu Fei, Wei Yi, Han Pingli, Yang Kui, Bai Lu, Shao Xiaoepeng
Opt Express. 2019 Feb 4;27(3):3629-3641. doi: 10.1364/OE.27.003629.
Underwater imaging provides human vision system friendly images; however, it often suffers from severe image degradation. This research developed an underwater polarization imaging model, which considers the water scattering effect, as well as absorption effect. It fully explored the polarization information of the target scene that backscattered light is partially polarized and target light is unpolarized. Then backscattered light is first estimated and removed. The target scene's distance information is derived based upon the polarization information, and then applied to develop a distance-based Lambertian model. This model enables estimation of the intensity loss caused by water absorption and accurate target radiance recovery. Furthermore, real-world experiments show that the developed model handled the underwater image degradation well. In particular, it enables effective color cast correction resulting from water absorption, which traditional imaging methods always ignore.
水下成像能够提供对人类视觉系统友好的图像；然而，它常常会遭受严重的图像退化。本研究开发了一种水下偏振成像模型，该模型考虑了水的散射效应以及吸收效应。它充分探究了目标场景的偏振信息，即后向散射光部分偏振而目标光非偏振。然后首先估计并去除后向散射光。基于偏振信息推导目标场景的距离信息，进而应用该信息来开发基于距离的朗伯模型。该模型能够估计由水吸收导致的强度损失并准确恢复目标辐射度。此外，实际实验表明所开发的模型能够很好地处理水下图像退化问题。特别地，它能够有效校正由水吸收引起的色偏，而这是传统成像方法一直忽略的。
