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Real-time underwater image enhancement: a systematic review

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Abstract

In recent years, deep sea and ocean explorations have attracted more attention in the marine industry. Most of the marine vehicles, including robots, submarines, and ships, would be equipped with automatic imaging of deep sea layers. There is a reason which the quality of the images taken by the underwater devices is not optimal due to water properties and impurities. Consequently, water absorbs a series of colors, so processing gets more difficult. Scattering and absorption are related to underwater imaging light and are called light attenuation in water. The examination has previously shown that the emergence of some inherent limitations is due to the presence of artifacts and environmental noise in underwater images. As a result, it is hard to distinguish objects from their backgrounds in those images in a real-time system. This paper discusses the effect of the software and hardware parts for the underwater image, surveys the state-of-art different strategies and algorithms in underwater image enhancement, and measures the algorithm performance from various aspects. We also consider the important conducted studies on the field of quality enhancement in underwater images. We have analyzed the methods from five perspectives: (a) hardware and software tools, (b) a variety of underwater imaging techniques, (c) improving real-time image quality, (d) identifying specific objectives in underwater imaging, and (e) assessments. Finally, the advantages and disadvantages of the presented real/non-real-time image processing techniques are addressed to improve the quality of the underwater images. This systematic review provides an overview of the major underwater image algorithms and real/non-real-time processing.

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Fig. 1

Source: Jaffe et al. [11]

Fig. 2

Source: Murez et al. [23]

Fig. 3

Source: Ghani et al. [29] and Iqbal et al. [36]

Fig. 4

Source: Abonaser et al. [38]

Fig. 5

Source: Ancuti et al. [46]

Fig. 6

Source: Ghani et al. [51] and Lu et al. [52]

Fig. 7

Source: Wang et al. [81]

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  1. Department of Communication Engineering, University of Sistan and Baluchestan, Zahedan, Iran

    Mohammad Kazem Moghimi & Farahnaz Mohanna

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Moghimi, M.K., Mohanna, F. Real-time underwater image enhancement: a systematic review. J Real-Time Image Proc 18, 1509–1525 (2021). https://doi.org/10.1007/s11554-020-01052-0

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