Autonomous Underwater Vehicles: Identifying Critical Issues and Future Perspectives in Image Acquisition

Monterroso Muñoz, Alberto; Moron-Fernández, Maria-Jose; Cascado-Caballero, Daniel; Diaz-del-Rio, Fernando; Real, Pedro

doi:10.3390/s23104986

Cited by 16 publications

(2 citation statements)

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“…Our method is intended to carry out underwater or undersea image and video restoration on underwater mobile systems, such as AOVs and UAVs [ 27 , 28 ]. In general, the hardware resource and computational ability of those devices show pretty poor performance, so the component of real time is challenging and significant.…”

Section: Results and Evaluationmentioning

confidence: 99%

Enhancement and Optimization of Underwater Images and Videos Mapping

Xiang

Wang

et al. 2023

Sensors

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Underwater images tend to suffer from critical quality degradation, such as poor visibility, contrast reduction, and color deviation by virtue of the light absorption and scattering in water media. It is a challenging problem for these images to enhance visibility, improve contrast, and eliminate color cast. This paper proposes an effective and high-speed enhancement and restoration method based on the dark channel prior (DCP) for underwater images and video. Firstly, an improved background light (BL) estimation method is proposed to estimate BL accurately. Secondly, the R channel’s transmission map (TM) based on the DCP is estimated sketchily, and a TM optimizer integrating the scene depth map and the adaptive saturation map (ASM) is designed to refine the afore-mentioned coarse TM. Later, the TMs of G–B channels are computed by their ratio to the attenuation coefficient of the red channel. Finally, an improved color correction algorithm is adopted to improve visibility and brightness. Several typical image-quality assessment indexes are employed to testify that the proposed method can restore underwater low-quality images more effectively than other advanced methods. An underwater video real-time measurement is also conducted on the flipper-propelled underwater vehicle-manipulator system to verify the effectiveness of the proposed method in the real scene.

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Section: Results and Evaluationmentioning

confidence: 99%

Enhancement and Optimization of Underwater Images and Videos Mapping

Xiang

Wang

et al. 2023

Sensors

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“…Vignetting effect: This refers to a reduction in the brightness or saturation of an image towards its periphery, as compared to the center of the image, as observed in Figure 2 [39].…”

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confidence: 99%

A Survey of Seafloor Characterization and Mapping Techniques

Loureiro,

Dias,

Almeida

et al. 2024

Remote Sensing

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The deep seabed is composed of heterogeneous ecosystems, containing diverse habitats for marine life. Consequently, understanding the geological and ecological characteristics of the seabed’s features is a key step for many applications. The majority of approaches commonly use optical and acoustic sensors to address these tasks; however, each sensor has limitations associated with the underwater environment. This paper presents a survey of the main techniques and trends related to seabed characterization, highlighting approaches in three tasks: classification, detection, and segmentation. The bibliography is categorized into four approaches: statistics-based, classical machine learning, deep learning, and object-based image analysis. The differences between the techniques are presented, and the main challenges for deep sea research and potential directions of study are outlined.

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