标题： 透过散射光线看世界：重新审视现实水下图像生成的图像形成模型 显示英文标题

标题： Sea-ing Through Scattered Rays: Revisiting the Image Formation Model for Realistic Underwater Image Generation

摘要： 近年来，水下图像形成模型在合成水下数据的生成中得到了广泛应用。 尽管许多方法主要关注受颜色变化影响的场景，但它们常常忽略了该模型捕捉高度浑浊环境中复杂、距离相关的能见度损失的能力。 在本工作中，我们提出了一个改进的合成数据生成流程，包括通常被忽略的前向散射项，同时考虑了非均匀介质。 此外，我们在控制浑浊条件下收集了BUCKET数据集，以获得相应的参考图像的真实浑浊视频。 我们的结果表明，在增加浑浊度的情况下，相对于参考模型有定性的改进，通过调查参与者的选择率达到了82.5%。 数据和代码可以在项目页面上访问：vap.aau.dk/sea-ing-through-scattered-rays. 显示英文摘要

摘要： In recent years, the underwater image formation model has found extensive use in the generation of synthetic underwater data. Although many approaches focus on scenes primarily affected by discoloration, they often overlook the model's ability to capture the complex, distance-dependent visibility loss present in highly turbid environments. In this work, we propose an improved synthetic data generation pipeline that includes the commonly omitted forward scattering term, while also considering a nonuniform medium. Additionally, we collected the BUCKET dataset under controlled turbidity conditions to acquire real turbid footage with the corresponding reference images. Our results demonstrate qualitative improvements over the reference model, particularly under increasing turbidity, with a selection rate of 82. 5\% by survey participants. Data and code can be accessed on the project page: vap.aau.dk/sea-ing-through-scattered-rays.