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Simulating shot noise of color underwater images
D.A. Shepelev 1,2, V.P. Bozhkova 1, E.I. Ershov 1, D.P. Nikolaev 1,3

1 Institute for Information Transmission Problems, RAS,
127051, Moscow, Russia, Bolshoy Karetny per. 19, build 1,
2 Moscow Institute of Physics and Technology,
141701, Dolgoprudny, Russia, Institutskiy per. 9,
3 LLC "Smart Engines Service",
117312, Moscow, Russia, Prospect 60-Letiya Oktyabrya 9

 PDF, 5109 kB

DOI: 10.18287/2412-6179-CO-754

Pages: 671-679.

Full text of article: Russian language.

Abstract:
This paper considers methods for simulating color underwater images based on real terrestrial images. Underwater image simulation is widely used for developing and testing methods for improving underwater images. A large group of existing methods uses the same deterministic image transformation model ignoring the presence of noise in images. The paper demonstrates that this significantly affects the overall quality of underwater images simulation. It is shown both theoretically and numerically that the accuracy of the signal-to-noise ratio of underwater images simulated using a deterministic transformation decreases with increasing distance to the object. To solve this problem, a new model of image transformation for simulating underwater images based on terrestrial images is proposed, which considers the presence of noise in the image and is compatible with all simulating methods from the group under consideration. The paper presents the results of the simulation based on the existing and proposed models, showing that at long distances, the new results are better consistent with real data.

Keywords:
underwater imaging, simulation of underwater images, noise simulation, color distortions, underwater image enhancement, color image augmentation, generating ground truth.

Citation:
Shepelev DA, Bozhkova VP, Ershov EI, Nikolaev DP. Simulating shot noise of color underwater images. Computer Optics 2020; 44(4): 671-679. DOI: 10.18287/2412-6179-CO-754.

Acknowledgements:
This work was carried out with a grant from the Russian Science Foundation (Project No. 20-61-47089).

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