Relevant bibliographies by topics / Underwater image acquisition

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Underwater image acquisition'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Underwater image acquisition"

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Gong, Benxing, and Guoyu Wang. "Underwater 2D Image Acquisition Using Sequential Striping Illumination." Applied Sciences 9, no. 11 (2019): 2179. http://dx.doi.org/10.3390/app9112179.

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Structured lighting techniques have increasingly been employed in underwater imaging, where scattering effects cannot be ignored. This paper presents an approach to underwater image recovery using structured light as a scanning mode. The method tackles both the forward scattering and back scattering problems. By integrating each of the sequentially striping illuminated frame images, we generate a synthesized image that can be modeled on the convolution of the surface albedo and the illumination function. Thus, image acquisition is issued as a problem of image recovery by deconvolution. The con
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Cheng, Peng, Jiang An Wang, Da Hui Qin, and Gui Yuan Mei. "The Underwater Bubbles Image’s Acquisition and Processing." Applied Mechanics and Materials 33 (October 2010): 152–56. http://dx.doi.org/10.4028/www.scientific.net/amm.33.152.

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Machine Vision was used to observer and measure the underwater bubbles. There are several ways been taken to solve many difficulties in the process of the acquisition to get the image. Such as the equipment selection, the light sources selection, the approach to images and the feature extraction of the image. The most important of them is the noise elimination and the extraction of the bubbles. The feature of the image can be very obviously after the Median filter and Sub-pixel edge detection. In this way, it provided an effective and feasible method to measure the underwater bubbles.
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Yang, Jiawei, Hongwu Huang, Fanchao Lin, Xiujing Gao, Junjie Jin, and Biwen Zhang. "Underwater Image Enhancement Fusion Method Guided by Salient Region Detection." Journal of Marine Science and Engineering 12, no. 8 (2024): 1383. http://dx.doi.org/10.3390/jmse12081383.

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Exploring and monitoring underwater environments pose unique challenges due to water’s complex optical properties, which significantly impact image quality. Challenges like light absorption and scattering result in color distortion and decreased visibility. Traditional underwater image acquisition methods face these obstacles, highlighting the need for advanced techniques to solve the image color shift and image detail loss caused by the underwater environment in the image enhancement process. This study proposes a salient region-guided underwater image enhancement fusion method to alleviate t
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Yasukawa, Shinsuke, Jonghyun Ahn, Yuya Nishida, Takashi Sonoda, Kazuo Ishii, and Tamaki Ura. "Vision System for an Autonomous Underwater Vehicle with a Benthos Sampling Function." Journal of Robotics and Mechatronics 30, no. 2 (2018): 248–56. http://dx.doi.org/10.20965/jrm.2018.p0248.

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We developed a vision system for an autonomous underwater robot with a benthos sampling function, specifically sampling-autonomous underwater vehicle (AUV). The sampling-AUV includes the following five modes: preparation mode (PM), observation mode (OM), return mode (RM), tracking mode (TM), and sampling mode (SM). To accomplish the mission objective, the proposed vision system comprises software modules for image acquisition, image enhancement, object detection, image selection, and object tracking. The camera in the proposed system acquires images in intervals of five seconds during OM and R
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Fu, Xianping, Xiaodi Shang, Xudong Sun, Haoyang Yu, Meiping Song, and Chein-I. Chang. "Underwater Hyperspectral Target Detection with Band Selection." Remote Sensing 12, no. 7 (2020): 1056. http://dx.doi.org/10.3390/rs12071056.

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Compared to multi-spectral imagery, hyperspectral imagery has very high spectral resolution with abundant spectral information. In underwater target detection, hyperspectral technology can be advantageous in the sense of a poor underwater imaging environment, complex background, or protective mechanism of aquatic organisms. Due to high data redundancy, slow imaging speed, and long processing of hyperspectral imagery, a direct use of hyperspectral images in detecting targets cannot meet the needs of rapid detection of underwater targets. To resolve this issue, a fast, hyperspectral underwater t
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Wang, Zhenfei, Meixin Hu, and Ketao Zhang. "Underwater Turbid Media Stokes-Based Polarimetric Recovery." Sensors 24, no. 5 (2024): 1367. http://dx.doi.org/10.3390/s24051367.

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Underwater optical imaging for information acquisition has always been an innovative and crucial research direction. Unlike imaging in the air medium, the underwater optical environment is more intricate. From an optical perspective, natural factors such as turbulence and suspended particles in the water cause issues like light scattering and attenuation, leading to color distortion, loss of details, decreased contrast, and overall blurriness. These challenges significantly impact the acquisition of underwater image information, rendering subsequent algorithms reliant on such data unable to fu
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Ji, Daxiong, Haichao Li, Chen-Wei Chen, Wei Song, and Shiqiang Zhu. "Visual detection and feature recognition of underwater target using a novel model-based method." International Journal of Advanced Robotic Systems 15, no. 6 (2018): 172988141880899. http://dx.doi.org/10.1177/1729881418808991.

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Imaging is an important means to explore the ocean for underwater robotics. The diffuse attenuation coefficient of light in water is one of the most important optical properties of seawater. This article presents a model-based method to analyze the causes of distortion of underwater images. We built a platform for underwater image acquisition and target recognition. The model coefficients were calibrated with images captured underwater and in air. Experiments were carried out to verify the designed algorithm and the transmission error model. The experiments show that the presented method works
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Monterroso Muñoz, Alberto, Maria-Jose Moron-Fernández, Daniel Cascado-Caballero, Fernando Diaz-del-Rio, and Pedro Real. "Autonomous Underwater Vehicles: Identifying Critical Issues and Future Perspectives in Image Acquisition." Sensors 23, no. 10 (2023): 4986. http://dx.doi.org/10.3390/s23104986.

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Underwater imaging has been present for many decades due to its relevance in vision and navigation systems. In recent years, advances in robotics have led to the availability of autonomous or unmanned underwater vehicles (AUVs, UUVs). Despite the rapid development of new studies and promising algorithms in this field, there is currently a lack of research toward standardized, general-approach proposals. This issue has been stated in the literature as a limiting factor to be addressed in the future. The key starting point of this work is to identify a synergistic effect between professional pho
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Yang, Dianyu, Jingfeng Yu, Can Wang, et al. "Side-Scan Sonar Image Matching Method Based on Topology Representation." Journal of Marine Science and Engineering 12, no. 5 (2024): 782. http://dx.doi.org/10.3390/jmse12050782.

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In the realm of underwater environment detection, achieving information matching stands as a pivotal step, forming an indispensable component for collaborative detection and research in areas such as distributed mapping. Nevertheless, the progress in studying the matching of underwater side-scan sonar images has been hindered by challenges including low image quality, intricate features, and susceptibility to distortion in commonly used side-scan sonar images. This article presents a comprehensive overview of the advancements in underwater sonar image processing. Building upon the novel Schema
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Zhao, Minghao, Chengquan Hu, Fenglin Wei, Kai Wang, Chong Wang, and Yu Jiang. "Real-Time Underwater Image Recognition with FPGA Embedded System for Convolutional Neural Network." Sensors 19, no. 2 (2019): 350. http://dx.doi.org/10.3390/s19020350.

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The underwater environment is still unknown for humans, so the high definition camera is an important tool for data acquisition at short distances underwater. Due to insufficient power, the image data collected by underwater submersible devices cannot be analyzed in real time. Based on the characteristics of Field-Programmable Gate Array (FPGA), low power consumption, strong computing capability, and high flexibility, we design an embedded FPGA image recognition system on Convolutional Neural Network (CNN). By using two technologies of FPGA, parallelism and pipeline, the parallelization of mul
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Dissertations / Theses on the topic "Underwater image acquisition"

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Liao, Shih-Chun, and 廖士竣. "A study of Pb(Zr0.52Ti0.48)O3 ultrasonic sensor installed in the Remotely Operated Vehicle for underwater image acquisition." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/mb44db.

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碩士<br>國立臺灣海洋大學<br>電機工程學系<br>105<br>In this paper, the ultrasonic sensor is fabricated by semiconductor process technology, and the lead zirconate titanate Pb(Zr0.52Ti0.48)O3 was used as the acoustic wave sensing layer. The focus of the research is to install the self-made ultrasonic sensor and 64 array ultrasonic transmitter in the Remotely Operated Vehicle (ROV) for underwater image acquisition, and the ultrasonic sensing device changes the sensing frequency by the structural adjustment of the piezoelectric layer and the upper and lower electrode layers, enhance the sonic wave receive intensi
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Book chapters on the topic "Underwater image acquisition"

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Ghosh, Bidisha, Michael O’Byrne, Franck Schoefs, and Vikram Pakrashi. "Fundamentals of image acquisition and imaging protocol." In Image-Based Damage Assessment for Underwater Inspections. CRC Press, 2018. http://dx.doi.org/10.1201/9781351052580-3.

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Batista, Ítalo Jáder Loiola, Antonio Themoteo Varela, Edicarla Pereira Andrade, et al. "A Mechatronic Description of an Autonomous Underwater Vehicle for Dam Inspection." In Mobile Ad Hoc Robots and Wireless Robotic Systems. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2658-4.ch010.

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Driven by the rising demand for underwater operations concerning dam structure monitoring, Hydropower Plant (HPP), reservoir, and lake ecosystem inspection, and mining and oil exploration, underwater robotics applications are increasing rapidly. The increase in exploration, prospecting, monitoring, and security in lakes, rivers, and the sea in commercial applications has led large companies and research centers to invest underwater vehicle development. The purpose of this work is to present the design of an Autonomous Underwater Vehicle (AUV), focusing efforts on dimensioning structural elemen
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Conference papers on the topic "Underwater image acquisition"

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Seo, Dongmin, Sangwoo Oh, and Seungoh Han. "Design of Biomimetic Optical Sensor for Underwater Fluid Velocity Measurement." In 3D Image Acquisition and Display: Technology, Perception and Applications. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/3d.2024.jm4a.1.

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To develop an optical sensor that mimics the neuromast, a sensory organ in the fish used to detect movement, vibration and pressure gradient, we propose a design of a pillar, a sensor structure with robust properties in the underwater, and present conditions and analysis results for simulating the displacement of the pillar in the flow field.
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Song, Guanglei, Qi Sun, Guanhua Wang, Huifeng Jiao, Yintao Wang, and Xinyu Qiu. "SAED-NET: A Novel Approach to Sonar Image Acquisition, Enhancement, and Detection of Small Underwater Target." In 2024 International Conference on Advanced Robotics and Mechatronics (ICARM). IEEE, 2024. http://dx.doi.org/10.1109/icarm62033.2024.10715897.

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Benzie, Philip, Hongyue Sun, and John Watson. "Holographic Image Acquisition and Remote Underwater Visualization." In OCEANS 2007 - Europe. IEEE, 2007. http://dx.doi.org/10.1109/oceanse.2007.4302446.

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Han, Jinlun, Hyoga Yamamoto, Yuya Nishida, and Shinsuke Yasukawa. "Time-Synchronized Projector–Camera System Design and Underwater Sharpening Image Acquisition Experiment." In 2023 IEEE Underwater Technology (UT). IEEE, 2023. http://dx.doi.org/10.1109/ut49729.2023.10103384.

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Martinho, Laura A., Odalisio L. S. Neto, João M. B. Calvalcanti, José L. S. Pio, and Felipe G. Oliveira. "An Approach for Fish Detection in Underwater Images." In Workshop de Visão Computacional. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/wvc.2023.27524.

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Underwater images are widely used for understanding subaquatic environments. However, underwater images are severely degraded by light absorption and scattering, as it propagates in water during image acquisition causing color distortion, low contrast and noise. These problems can interfere in underwater vision tasks, such as recognition and detection. In this paper we propose an approach for fish detection in underwater environments. In order to achieve this goal, the proposed method is composed by two main steps: i) Image Restoration, processing the underwater images to enhance the image qua
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Benger, Marc, Jostein Thorstensen, Igor Abrosimov, et al. "UTOFIA: an underwater time-of-flight image acquisition system." In Electro-Optical Remote Sensing, edited by Gary Kamerman and Ove Steinvall. SPIE, 2017. http://dx.doi.org/10.1117/12.2277944.

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Kulkarni, Indraneel S., and Dario Pompili. "Coordination of autonomous underwater vehicles for acoustic image acquisition." In the third ACM international workshop. ACM Press, 2008. http://dx.doi.org/10.1145/1410107.1410113.

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Joshi, Rakesh, and Bahram Javidi. "Three-dimensional Integral Imaging Visualization in Scattering Medium with Active Polarization Descattering." In 3D Image Acquisition and Display: Technology, Perception and Applications. Optica Publishing Group, 2023. http://dx.doi.org/10.1364/3d.2023.jtu4a.39.

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We present an integral image-based polarization descattering for underwater object visualization. Reconstruction based on integral imaging reduces noise and improves the estimation of the intermediate parameters required for polarization-based image recovery.
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Yamamoto, Hirotsugu, Kenta Onuki, and Sho Onose. "Forming Underwater Information Display with Aerial Imaging by Retro-Reflection (AIRR)." In 3D Image Acquisition and Display: Technology, Perception and Applications. OSA, 2018. http://dx.doi.org/10.1364/3d.2018.3m5g.4.

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Javidi, Bahram. "Sensing, Visualization, and Recognition in Degraded Environment using Passive Multidimensional Integral Imaging (Keynote Address)." In 3D Image Acquisition and Display: Technology, Perception and Applications. Optica Publishing Group, 2023. http://dx.doi.org/10.1364/3d.2023.dm2a.1.

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This keynote-address presents an overview of passive multidimensional integral-imaging for sensing, visualization, and recognition in degraded-environments including turbid underwater signal detection, 3D visualization in low-light, fog, and obscurations, gesture-recognition, long-wave IR imaging, and depth estimation.
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