Sea-Undistort：用于高分辨率航空测深制图中水下图像复原的数据集
Sea-Undistort: A Dataset for Through-Water Image Restoration in High Resolution Airborne Bathymetric Mapping
AI总结：
针对浅水区航空测深制图中光学畸变导致的水下图像复原难题，提出含1200对场景的合成数据集Sea-Undistort，基于其基准测试增强型轻量级扩散框架，该框架应用于真实数据时能提升海床DSM完整性、降低误差并复原细节。
摘要：
由于动态水面、水体特性和太阳光照引入的波浪诱导图案、散射和太阳眩光等复杂光学畸变，浅水区基于图像的精确测深制图仍具挑战性。本研究提出Sea-Undistort，这是一个包含1200对512x512水下场景的综合合成数据集，通过Blender渲染。每对场景包含无畸变视图和畸变视图，具有真实的水面效果，如太阳眩光、波浪和不同海床上的散射，还附有相机参数、太阳位置和平均深度等单图像元数据，使在真实环境中不可行的监督训练成为可能。研究使用该数据集对两种最先进的图像复原方法，以及一个带有早期融合太阳眩光掩码的增强型轻量级扩散框架进行基准测试。将增强型扩散模型应用于真实航空数据时，可生成更完整的海床数字表面模型（DSM）（尤其是在较深区域），减少测深误差，抑制眩光和散射，并清晰复原海床精细细节。数据集、权重和代码可在https://www.magicbathy.eu/Sea-Undistort.html公开获取。
英文摘要：
Accurate image-based bathymetric mapping in shallow waters remains challenging due to the complex optical distortions such as wave induced patterns, scattering and sunglint, introduced by the dynamic water surface, the water column properties, and solar illumination. In this work, we introduce Sea-Undistort, a comprehensive synthetic dataset of 1200 paired 512x512 through-water scenes rendered in Blender. Each pair comprises a distortion-free and a distorted view, featuring realistic water effects such as sun glint, waves, and scattering over diverse seabeds. Accompanied by per-image metadata such as camera parameters, sun position, and average depth, Sea-Undistort enables supervised training that is otherwise infeasible in real environments. We use Sea-Undistort to benchmark two state-of-the-art image restoration methods alongside an enhanced lightweight diffusion-based framework with an early-fusion sun-glint mask. When applied to real aerial data, the enhanced diffusion model delivers more complete Digital Surface Models (DSMs) of the seabed, especially in deeper areas, reduces bathymetric errors, suppresses glint and scattering, and crisply restores fine seabed details. Dataset, weights, and code are publicly available at https://www.magicbathy.eu/Sea-Undistort.html.
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