Marine Snow Removal Benchmarking Dataset
- URL: http://arxiv.org/abs/2103.14249v3
- Date: Sat, 13 Jan 2024 01:04:58 GMT
- Title: Marine Snow Removal Benchmarking Dataset
- Authors: Reina Kaneko, Yuya Sato, Takumi Ueda, Hiroshi Higashi, Yuichi Tanaka
- Abstract summary: This paper introduces a new benchmarking dataset for marine snow removal of underwater images.
We mathematically model two typical types of marine snow from the observations of real underwater images.
We propose two marine snow removal tasks using the dataset and show the first benchmarking results of marine snow removal.
- Score: 9.117162374919715
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: This paper introduces a new benchmarking dataset for marine snow removal of
underwater images. Marine snow is one of the main degradation sources of
underwater images that are caused by small particles, e.g., organic matter and
sand, between the underwater scene and photosensors. We mathematically model
two typical types of marine snow from the observations of real underwater
images. The modeled artifacts are synthesized with underwater images to
construct large-scale pairs of ground truth and degraded images to calculate
objective qualities for marine snow removal and to train a deep neural network.
We propose two marine snow removal tasks using the dataset and show the first
benchmarking results of marine snow removal. The Marine Snow Removal
Benchmarking Dataset is publicly available online.
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