Sea-ing Through Scattered Rays: Revisiting the Image Formation Model for Realistic Underwater Image Generation
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866912594157109248 |
|---|---|
| author | Ismiroglou, Vasiliki Pedersen, Malte Bengtson, Stefan H. Aakerberg, Andreas Moeslund, Thomas B. |
| author_facet | Ismiroglou, Vasiliki Pedersen, Malte Bengtson, Stefan H. Aakerberg, Andreas Moeslund, Thomas B. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_15011 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Sea-ing Through Scattered Rays: Revisiting the Image Formation Model for Realistic Underwater Image Generation Ismiroglou, Vasiliki Pedersen, Malte Bengtson, Stefan H. Aakerberg, Andreas Moeslund, Thomas B. Computer Vision and Pattern Recognition Artificial Intelligence 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. |
| title | Sea-ing Through Scattered Rays: Revisiting the Image Formation Model for Realistic Underwater Image Generation |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2509.15011 |