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

Vasiliki Ismiroglou, Malte Pedersen, Stefan H. Bengtson, Andreas Aakerberg, Thomas B. Moeslund
9/18/2025
cs.CVcs.AI

No official code found. Best implementation: vismiroglou/STSR (6 stars, MIT, last commit 2026-02-03).

Abstract

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.

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vismiroglou/STSRCommunity61%
MIT

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

60PythonSep 18, 20258 months agoMIT
image-formation-modelsynthetic-dataturbidityunderwater-vision

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Cite this paper

@article{ismiroglou2025seaing,
  title  = {Sea-ing Through Scattered Rays: Revisiting the Image Formation Model for Realistic Underwater Image Generation},
  author = {Vasiliki Ismiroglou and Malte Pedersen and Stefan H. Bengtson and Andreas Aakerberg and Thomas B. Moeslund},
  year   = {2025},
  eprint = {2509.15011},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2509.15011v2}
}

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