• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2552-2570
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• 2022

Underwater images usually have various problems, such as the color cast of underwater images due to the attenuation of different lights in water, the darkness of image caused by the lack of light underwater, and the haze effect of underwater images because of the scattering of light. To address the above problems, the channel attention mechanism, strengthen-operate-subtract (SOS) boosting mechanism and gated fusion module are introduced in our paper, based on which, an underwater image recovery network is proposed. First, for the color cast problem of underwater images, the channel attention mechanism is incorporated in our model, which can well alleviate the color cast of underwater images. Second, as for the darkness of underwater images, the similarity between the target underwater image after dehazing and color correcting, and the image output by our model is used as the loss function, so as to increase the brightness of the underwater image. Finally, we employ the SOS boosting module to eliminate the haze effect of underwater images. Moreover, experiments were carried out to evaluate the performance of our model. The qualitative analysis results show that our method can be applied to effectively recover the underwater images, which outperformed most methods for comparison according to various criteria in the quantitative analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.544-564
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• 2022

Underwater images often suffer from color distortion, blurring and low contrast, which is caused by the propagation of light in the underwater environment being affected by the two processes: absorption and scattering. To cope with the poor quality of underwater images, this paper proposes a multiscale fusion underwater image enhancement method based on channel attention mechanism and local binary pattern (LBP). The network consists of three modules: feature aggregation, image reconstruction and LBP enhancement. The feature aggregation module aggregates feature information at different scales of the image, and the image reconstruction module restores the output features to high-quality underwater images. The network also introduces channel attention mechanism to make the network pay more attention to the channels containing important information. The detail information is protected by real-time superposition with feature information. Experimental results demonstrate that the method in this paper produces results with correct colors and complete details, and outperforms existing methods in quantitative metrics.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.148-158
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• 2015

It is difficult to test a detection system in underwater acoustics channel environments. The system can be evaluated by using simulation analysis tool. In this paper, a simulation tool is proposed to analyze the effectiveness of underwater acoustics detection based on database for real environments. First, the underwater environment is built based on HYCOM underwater environment database. Then, a multipath characteristic is considered through calculating underwater acoustics propagation path/pressure based on the ray theory. Also, hydrophone thermal noise and underwater ambient noise are considered to reflect underwater noise characteristics.

• Journal of Ocean Engineering and Technology
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• v.30 no.3
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• pp.227-233
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• 2016

This paper presents an underwater structure 3D reconstruction method using a 2D multibeam imaging sonar. Compared with other underwater environmental recognition sensors, the 2D multibeam imaging sonar offers high resolution images in water with a high turbidity level by showing the reflection intensity data in real-time. With such advantages, almost all underwater applications, including ROVs, have applied this 2D multibeam imaging sonar. However, the elevation data are missing in sonar images, which causes difficulties with correctly understanding the underwater topography. To solve this problem, this paper concentrates on the physical relationship between the sonar image and the scene topography to find the elevation information. First, the modeling of the sonar reflection intensity data is studied using the distances and angles of the sonar beams and underwater objects. Second, the elevation data are determined based on parameters like the reflection intensity and shadow length. Then, the elevation information is applied to the 3D underwater reconstruction. This paper evaluates the presented real-time 3D reconstruction method using real underwater environments. Experimental results are shown to appraise the performance of the method. Additionally, with the utilization of ROVs, the contour and texture image mapping results from the obtained 3D reconstruction results are presented as applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.327-329
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• 2021

Underwater acoustic communication channel is influenced by environmental parameters such as multipath, background noise and scattering. Therefore, a transmitted signal is influenced by the sea surface and the sea bottom boundaries, and a received signal shows a delay spread. These factors create a noise in the image and degrade the quality of underwater acoustic communication. To solve these problems, in this paper, we evaluate the performance of an underwater acoustic communication model using a denoising auto-encoder used for unsupervised learning. Noise images generated by the underwater multipath channel were collected and used as training data. Experimental results were analyzed as a PSNR parameter that expressed the noise ratio of the two images.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.163-167
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• 2010

In underwater acoustic communication, acoustic signals from transducers or hydrophones are used. And the underwater acoustic communication channels are very complicated, because of vertical distribution of acoustic velocity according depths, and reflections from boundaries like as surface or bottom. For the implementation of the underwater acoustic communication channel, the image method or ray tracing method have been used. In this paper, we introduce a new approach for implementation of underwater acoustic communication channel using the simulation of the Transmission Line Matrix Modeling and cross-correlations from the input and output signals.

• Journal of Korea Multimedia Society
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• v.18 no.4
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• pp.506-523
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• 2015

The intent is to determine whether or not the custody transfer is helpful for data transmission in challenging underwater communications when running Bundle protocol or underwater protocols. From the point of view defending side, Underwater Acoustic Network (UAN) will be a serious threat for its strong functionality long rang and high precision of surveillance and detection. Therefore, countermeasures must be taken to weaken its effect. Our purpose is analyzed that how to benefit from the UIoT to learn from, exploit and preserve the natural underwater resources. Delay/Disruption Tolerant Network (DTN) is essential part of the network heterogeneity communication network. The vulnerability and potential security factors of UIoT are studied thereafter. Security mechanisms for an underwater environment are difficult to apply owing to the limited bandwidth. Therefore, for underwater security, appropriate security mechanisms and security requirements must be defined simultaneously. The paper consists of mathematical and security model. Most important point of view in the security challenges of effective Buffer and Storage management in DTN.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.3
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• pp.256-265
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• 2017

In this paper, an ascheme is proposed for multiuser underwater acoustic communication by using the multi-chirp rate signals. It differs from the well known TDMA (Time Division Multiple Access), FDMA (Frequency Division Multiple Access) or CDMA (Code Division Multiple Access), by assigning each users with different chirp-rate carriers instead of the time, frequency or PN code. Multi-chirp rate signals can be separated from each other by FrFT (Fractional Fourier Transform), which can be regarded as the chirp-based decomposing, and superior to the match filter in the underwater acoustic channel. VTRM (Virtual Time Reverse Mirror) is applied into the system to alleviate the ISI caused by the multipatch and make the equalization more simple. Results of computer simulations and pool experiments prove that the proposed multiuser underwater acoustic communication based on the multi-chirp rate exhibit well performance. Outfield experments carrie out in Xiamen Port show that using about 10 kHz bandwidth, four users could communicate at the same time with 425 bps with low BER and can match the UAC application.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.1
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• pp.38-44
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• 2011

Because of the complexity of the underwater environment, the communication has difficulties that can differ significantly from those in air, The signal is degraded by many random noises. Furthermore, the limit of the bandwidth is a big issue in underwater communication. Therefore, the array signal processing can be adapted to improve the signal-to-noise ratio. In this paper, we propose a potential method for underwater communication based upon source tracking techniques. Also, a new tracking model by using a multi-array sonar and detail of the multi-array sonar configuration are shown in this paper. The experiment results demonstrated the receiver configuration is very potential to solve communication problems, especially in the underwater environment.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.91-98
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• 2016

Detection and classification of underwater objects in sonar imagery are challenging problems. This paper proposes a system that detects and identifies underwater objects at the sea floor level using a sonar image and image processing techniques. The identification process of underwater objects consists of two steps; detection of candidate regions and identification of underwater objects. The candidate regions of underwater objects are extracted by image registration through the detection of common feature points between the reference background image and the current scanning image. And then, underwater objects are identified as the closest pattern within the database using eigenvectors and eigenvalues as features. The proposed system is expected to be used in efficient securement of Q route in vessel navigation.