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

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/seaing-through-scattered-rays.

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Publication Details

Published
2025-10-19
DOI
https://doi.org/10.1109/iccvw69036.2025.00219
Primary Topic
Image Enhancement Techniques
Type
article
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article

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

Image Enhancement Techniques
article

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

article en

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/seaing-through-scattered-rays.

Aalborg University (DK)
Life below water
Openalex Percentile: Top 27%
Image Enhancement Techniques
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