Signals and Images in Sea Technologies

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (1 August 2020) | Viewed by 19216

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Special Issue Editors


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Guest Editor
Institute of Information Science and Technologies, National Research Council of Italy, Signals and Images Laboratory, Via Moruzzi, 1, 56124 Pisa, Italy
Interests: computational intelligence and intelligent systems; artificial intelligence; computer vision; multimedia information processing; signal processing; assistive technologies; interactive systems and augmented reality
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Institute of Information Science and Technologies, National Research Council of Italy, Signals and Images Laboratory, Via Moruzzi, 1-56124 Pisa, Italy
Interests: image analysis and understanding; multimedia information systems; spatial modeling and intelligent processes in computer vision and information technology; sea technologies and applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue includes papers that aim at combining technology and scientific research related to the sea with the typical standards of the Information and Communication Technologies (ICT) domain.

Generally, the sectors of ICT have been combined with the scientific and technological research activities on the sea for some time now, and they are related, among others, to the fields of:

-       Sensors for environmental monitoring (physical–chemical parameters, marine pollution, eutrophication ecotoxicology);

-       Submarine robotics (AUV—autonomous underwater vehicles, ROV—remotely operated vehicles, etc.);

-       Monitoring of sea geomorphology, maritime activities, and navigation using remote sensors (radar/optical/satellite instruments) mounted on satellites, coastal structures, flying platforms (aircraft–helicopters), and ships;

-       Coastal oceanography, for the measurement of wave motion and coastal erosion and related sensors;

-       Development of imaging techniques for underwater mapping, underwater archeology, submarine research, and structural monitoring and inspections;

-       Development of mathematical, hydrofluid dynamic models for oceanography and related sensors;

-       Physical oceanographic and submarine geophysics;

-       Marine biology and aquaculture;

-       Marine meteorology and study of the sea–atmosphere interface;

-       Climate changes and related monitoring;

-       Study of the anthropic impact on the marine environment.

This relation derives from an approach that moves from so-called ocean engineering (study of applied engineering techniques to the scientific disciplines inherent in seas and oceans) towards ICT requirements.

In our case, this Special Issue intends to investigate the reverse path, i.e., to exploit the techniques and the ICT approaches, and in particular the study and application of signal- and image-based methods, and to explore the advantages of their application to the areas mentioned above.

In particular, this Special Issue seeks original contributions that address and discuss the impact and relevance of signals and images treatment and processing in R&D areas such as:

-       Oceanographic engineering;

-       Sensor and marine monitoring;

-       Marine robotics;

-       Optical and acoustic image analysis;

-       Virtual and augmented reality for sea investigation;

-       Human–sea interaction.

In addition to the abovementioned topics, innovative and breakthrough contributions based on the convergence of signal and image processing, analysis, and understanding in any challenging sea application are welcome.

Dr. Davide Moroni
Dr. Ovidio Salvetti
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Optical and acoustic image analysis
  • Multimodal sensor data processing
  • Multidimensional signal processing and analysis
  • Sensor data fusion
  • Sensor networks and communication aspects
  • Multispectral and hyperspectral imaging
  • Patter recognition and machine learning methods

Published Papers (7 papers)

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Editorial

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3 pages, 143 KiB  
Editorial
Signals and Images in Sea Technologies
by Davide Moroni and Ovidio Salvetti
J. Mar. Sci. Eng. 2021, 9(1), 41; https://doi.org/10.3390/jmse9010041 - 04 Jan 2021
Cited by 1 | Viewed by 1324
Abstract
Life below water is the 14th Sustainable Development Goal (SDG) envisaged by the United Nations and is aimed at conserving and sustainably using the oceans, seas and marine resources for sustainable development [...] Full article
(This article belongs to the Special Issue Signals and Images in Sea Technologies)

Research

Jump to: Editorial

23 pages, 1453 KiB  
Article
An Underwater Image Enhancement Algorithm Based on MSR Parameter Optimization
by Kai Hu, Yanwen Zhang, Feiyu Lu, Zhiliang Deng and Yunping Liu
J. Mar. Sci. Eng. 2020, 8(10), 741; https://doi.org/10.3390/jmse8100741 - 25 Sep 2020
Cited by 16 | Viewed by 3057
Abstract
The quality of underwater images is often affected by the absorption of light and the scattering and diffusion of floating objects. Therefore, underwater image enhancement algorithms have been widely studied. In this area, algorithms based on Multi-Scale Retinex (MSR) represent an important research [...] Read more.
The quality of underwater images is often affected by the absorption of light and the scattering and diffusion of floating objects. Therefore, underwater image enhancement algorithms have been widely studied. In this area, algorithms based on Multi-Scale Retinex (MSR) represent an important research direction. Although the visual quality of underwater images can be improved to some extent, the enhancement effect is not good due to the fact that the parameters of these algorithms cannot adapt to different underwater environments. To solve this problem, based on classical MSR, we propose an underwater image enhancement optimization (MSR-PO) algorithm which uses the non-reference image quality assessment (NR-IQA) index as the optimization index. First of all, in a large number of experiments, we choose the Natural Image Quality Evaluator (NIQE) as the NR-IQA index and determine the appropriate parameters in MSR as the optimization object. Then, we use the Gravitational Search Algorithm (GSA) to optimize the underwater image enhancement algorithm based on MSR and the NIQE index. The experimental results show that this algorithm has an excellent adaptive ability to environmental changes. Full article
(This article belongs to the Special Issue Signals and Images in Sea Technologies)
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18 pages, 3249 KiB  
Article
A Layout Strategy for Distributed Barrage Jamming against Underwater Acoustic Sensor Networks
by Mengchen Xiong, Jie Zhuo, Yangze Dong and Xin Jing
J. Mar. Sci. Eng. 2020, 8(4), 252; https://doi.org/10.3390/jmse8040252 - 03 Apr 2020
Cited by 6 | Viewed by 2507
Abstract
Underwater acoustic sensor networks (UASNs) can effectively detect and track targets and therefore play an important role in underwater detection technology. To protect a target from being detected by UASNs, a distributed barrage jamming layout strategy is proposed, which considers the detection performance [...] Read more.
Underwater acoustic sensor networks (UASNs) can effectively detect and track targets and therefore play an important role in underwater detection technology. To protect a target from being detected by UASNs, a distributed barrage jamming layout strategy is proposed, which considers the detection performance of UASNs as an indicator of the jamming performance. Since common indices of detection performance often involve specific signal processing methods, the Cramér–Rao bound (CRB) of multiple targets estimated by an UASN for distributed jammers is deduced in this paper, which is universal for all signal processing methods. The optimization model of the distributed jamming layout strategy is designed by maximizing the CRB to achieve the best jamming effect with limited jammers. A heuristic algorithm is used to solve this optimization model, and a numerical simulation shows that the optimal layout strategy for distributed jammers proposed in this paper achieves better performance than traditional jamming layout strategies. Considering the deviation of the position of the jammers from the ideal value due to the movement of water in a real marine environment, this paper also analyzes the jamming effects of strategies when there is error in the position of the jammers. The result proves the effectiveness and superiority of the proposed optimal layout strategy in an actual environment. Full article
(This article belongs to the Special Issue Signals and Images in Sea Technologies)
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28 pages, 2162 KiB  
Article
Improving the Performance of Dynamic Ship Positioning Systems: A Review of Filtering and Estimation Techniques
by Denis Selimović, Jonatan Lerga, Jasna Prpić-Oršić and Sasa Kenji
J. Mar. Sci. Eng. 2020, 8(4), 234; https://doi.org/10.3390/jmse8040234 - 30 Mar 2020
Cited by 7 | Viewed by 3964
Abstract
Various operations at sea, such as maintaining a constant ship position and direction, require a complex control system. Under such conditions, the ship needs an efficient positioning technique. Dynamic positioning (DP) systems provide such an application with a combination of the actuators mechanism, [...] Read more.
Various operations at sea, such as maintaining a constant ship position and direction, require a complex control system. Under such conditions, the ship needs an efficient positioning technique. Dynamic positioning (DP) systems provide such an application with a combination of the actuators mechanism, analyses of crucial ship variables, and environmental conditions. The natural forces of induced nonlinear waves acting on a ship’s hull interfere with the systems. To generate control signals for actuators accurately, sensor measurements should be filtered and processed. Furthermore, for safe and green routing, the forces and moments acting on the ship’s hull should be taken into account in terms of their prediction. Thus, the design of such systems takes into account the problem of obtaining data about the directional wave spectra (DWS). Sensor systems individually cannot provide high accuracy and reliability, so their measurements need to be combined and complemented. Techniques based on the recursive Kalman filter (KF) are used for this purpose. When some measurements are unavailable, the estimation procedure should predict them and, based on the comparison of theoretical and measured states, reduce the error variance of the analyzed signals. Different approaches for improving estimation algorithms have evolved over the years with the indication of improvement. This paper gives an overview of the state-of-the-art estimation and filtering techniques for providing optimum estimation states in DP systems. Full article
(This article belongs to the Special Issue Signals and Images in Sea Technologies)
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12 pages, 1332 KiB  
Article
Optimized Dislocation of Mobile Sensor Networks on Large Marine Environments Using Voronoi Partitions
by Mario D’Acunto, Davide Moroni, Alessandro Puntoni and Ovidio Salvetti
J. Mar. Sci. Eng. 2020, 8(2), 132; https://doi.org/10.3390/jmse8020132 - 18 Feb 2020
Cited by 6 | Viewed by 2065
Abstract
The real-time environmental surveillance of large areas requires the ability to dislocate sensor networks. Generally, the probability of the occurrence of a pollution event depends on the burden of possible sources operating in the areas to be monitored. This implies a challenge for [...] Read more.
The real-time environmental surveillance of large areas requires the ability to dislocate sensor networks. Generally, the probability of the occurrence of a pollution event depends on the burden of possible sources operating in the areas to be monitored. This implies a challenge for devising optimal real-time dislocation of wireless sensor networks. This challenge involves both hardware solutions and algorithms optimizing the displacements of mobile sensor networks in large areas with a vast number of sources of pollutant factors based mainly on diffusion mechanisms. In this paper, we present theoretical and simulated results inherent to a Voronoi partition approach for the optimized dislocation of a set of mobile wireless sensors with circular (radial) sensing power on large areas. The optimal deployment was found to be a variation of the generalized centroidal Voronoi configuration, where the Voronoi configuration is event-driven, and the centroid set of the corresponding generalized Voronoi cells changes as a function of the pollution event. The initial localization of the pollution events is simulated with a Poisson distribution. Our results could improve the possibility of reducing the costs for real-time surveillance of large areas, and other environmental monitoring when wireless sensor networks are involved. Full article
(This article belongs to the Special Issue Signals and Images in Sea Technologies)
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15 pages, 4551 KiB  
Article
On the Estimation of the Surface Elevation of Regular and Irregular Waves Using the Velocity Field of Bubbles
by Diana Vargas, Ravindra Jayaratne, Edgar Mendoza and Rodolfo Silva
J. Mar. Sci. Eng. 2020, 8(2), 88; https://doi.org/10.3390/jmse8020088 - 02 Feb 2020
Cited by 6 | Viewed by 2111
Abstract
This paper describes a new set of experiments focused on estimating time series of the free surface elevation of water (FSEW) from velocities recorded by submerged air bubbles under regular and irregular waves using a low-cost non-intrusive technique. The main purpose is to [...] Read more.
This paper describes a new set of experiments focused on estimating time series of the free surface elevation of water (FSEW) from velocities recorded by submerged air bubbles under regular and irregular waves using a low-cost non-intrusive technique. The main purpose is to compute wave heights and periods using time series of velocities recorded at any depth. The velocities were taken from the tracking of a bubble curtain with only one high-speed digital video camera and a bubble generator. These experiments eliminate the need of intrusive instruments while the methodology can also be applied if the free surface is not visible or even if only part of the depth can be recorded. The estimation of the FSEW was successful for regular waves and reasonably accurate for irregular waves. Moreover, the algorithm to reconstruct the FSEW showed better results for larger wave amplitudes. Full article
(This article belongs to the Special Issue Signals and Images in Sea Technologies)
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16 pages, 2068 KiB  
Article
Robust Capon Beamforming against Steering Vector Error Dominated by Large Direction-of-Arrival Mismatch for Passive Sonar
by Yu Hao, Nan Zou and Guolong Liang
J. Mar. Sci. Eng. 2019, 7(3), 80; https://doi.org/10.3390/jmse7030080 - 26 Mar 2019
Cited by 13 | Viewed by 3381
Abstract
Capon beamforming is often applied in passive sonar to improve the detectability of weak underwater targets. However, we often have no accurate prior information of the direction-of-arrival (DOA) of the target in the practical applications of passive sonar. In this case, Capon beamformer [...] Read more.
Capon beamforming is often applied in passive sonar to improve the detectability of weak underwater targets. However, we often have no accurate prior information of the direction-of-arrival (DOA) of the target in the practical applications of passive sonar. In this case, Capon beamformer will suffer from performance degradation due to the steering vector error dominated by large DOA mismatch. To solve this, a new robust Capon beamforming approach is proposed. The essence of the proposed method is to decompose the actual steering vector into two components by oblique projection onto a subspace and then estimate the actual steering vector in two steps. First, we estimate the oblique projection steering vector within the subspace by maximizing the output power while controlling the power from the sidelobe region. Subsequently, we search for the actual steering vector within the neighborhood of the estimated oblique projection steering vector by maximizing the output signal-to-interference-plus-noise ratio (SINR). Semidefinite relaxation and Charnes-Cooper transformation are utilized to derive convex formulations of the estimation problems, and the optimal solutions are obtained by the rank-one decomposition theorem. Numerical simulations demonstrate that the proposed method can provide superior performance, as compared with several previously proposed robust Capon beamformers in the presence of large DOA mismatch and other array imperfections. Full article
(This article belongs to the Special Issue Signals and Images in Sea Technologies)
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