ReviewJournal of imaging2025
From Physically Based to Generative Models: A Survey on Underwater Image Synthesis Techniques.
Review in Journal of imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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0 citing papers in PubMed.
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Authors and funding
2 authors.
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Abstract
The underwater world has gained significant attention in research in recent years, particularly in the context of ocean exploration. Images serve as a valuable data source for underwater tasks, but they face several issues related to light behavior in this environment. Given the complexity of capturing data from the sea and the large variability of environmental components (depth, distance, suspended particles, turbidity, etc.), synthesized underwater scenes can provide relevant data to improve image processing algorithms and computer vision tasks. The main goal of this survey is to summarize techniques to underwater image synthesis, their contributions and correlations, and to highlight further directions and opportunities in this research domain.
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