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Journal articles on the topic 'Side scan sonars'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Bikonis, Krzysztof, Marek Moszynski, and Zbigniew Lubniewski. "Application of Shape From Shading Technique for Side Scan Sonar Images." Polish Maritime Research 20, no. 3 (2013): 39–44. http://dx.doi.org/10.2478/pomr-2013-0033.

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Abstract Digital signal processing technology has revolutionized a way of processing, visualisation and interpretation of data acquired by underwater systems. Through many years side scan sonars were one of the most widely used imaging systems in the underwater environment. Although they are relatively cheap and easy to deploy, more powerful sensors like multibeam echo sounders and sonars are widely used today and deliver 3D bathymetry of sea bottom terrain. Side scan sonar outputs data usually in a form of grey level 2D acoustic images but the analysis of such pictures performed by human eye

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2

Ye, Xiufen, Haibo Yang, Chuanlong Li, Yunpeng Jia, and Peng Li. "A Gray Scale Correction Method for Side-Scan Sonar Images Based on Retinex." Remote Sensing 11, no. 11 (2019): 1281. http://dx.doi.org/10.3390/rs11111281.

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When side-scan sonars collect data, sonar energy attenuation, the residual of time varying gain, beam patterns, angular responses, and sonar altitude variations occur, which lead to an uneven gray level in side-scan sonar images. Therefore, gray scale correction is needed before further processing of side-scan sonar images. In this paper, we introduce the causes of gray distortion in side-scan sonar images and the commonly used optical and side-scan sonar gray scale correction methods. As existing methods cannot effectively correct distortion, we propose a simple, yet effective gray scale corr

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3

Yan, Jun, Junxia Meng, and Jianhu Zhao. "Bottom Detection from Backscatter Data of Conventional Side Scan Sonars through 1D-UNet." Remote Sensing 13, no. 5 (2021): 1024. http://dx.doi.org/10.3390/rs13051024.

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As widely applicated in many underwater research fields, conventional side-scan sonars require the sonar height to be at the seabed for geocoding seabed images. However, many interference factors, including compensation with unknown gains, suspended matters, etc., would bring difficulties in bottom detection. Existing methods need manual parameter setups or to use postprocessing methods, which limits automatic and real-time processing in complex situations. To solve this problem, a one-dimensional U-Net (1D-UNet) model for sea bottom detection of side-scan data and the bottom detection and tra

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4

Alekseev, G. G., E. A. Alekseeva, A. P. Sorokin, and S. A. Sorokin. "Complex of morphological analysis of images for side-scan sonar on basis of Griffon hardware platform." Issues of radio electronics 49, no. 9 (2020): 30–37. http://dx.doi.org/10.21778/2218-5453-2020-9-30-37.

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The article describes the developed computational complex of morphological image analysis for interferometric side-scan sonars. Examples of modeling the operation of the side-scan sonar in cases where the structure of bottom sediments is not known in advance are given. The results of the analysis of experimental data are considered. A description is given of the structure for constructing algorithms for morphological image analysis used in the operation of the complex. Recommendations are given on the effective use of the computing capabilities of the Griffon hardware platform for organizing p

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5

Trevorrow, Mark V., and Ian J. Booth. "Extraction of Ocean Wave Directional Spectra Using Steerable Doppler Side-Scan Sonars." Journal of Atmospheric and Oceanic Technology 12, no. 5 (1995): 1087–100. http://dx.doi.org/10.1175/1520-0426(1995)012<1087:eoowds>2.0.co;2.

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6

Bruce, M. P. "A processing requirement and resolution capability comparison of side-scan and synthetic-aperture sonars." IEEE Journal of Oceanic Engineering 17, no. 1 (1992): 106–17. http://dx.doi.org/10.1109/48.126959.

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7

Bikonis, Krzysztof, Andrzej Stepnowski, and Marek Moszynski. "Computer Vision Techniques Applied for Reconstruction of Seafloor 3D Images from Side Scan and Synthetic Aperture Sonars Data." Journal of the Acoustical Society of America 123, no. 5 (2008): 3748. http://dx.doi.org/10.1121/1.2935303.

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8

Witos-Okrasińska, Dominika, Grażyna Grelowska, and Eugeniusz Kozaczka. "Influence of Natural Conditions on the Imaging of the Bottom of the Gdańsk Bay by Means of the Side Scan Sonar." Polish Maritime Research 25, s1 (2018): 104–10. http://dx.doi.org/10.2478/pomr-2018-0030.

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Abstract The interest in underwater resources is the reason for the development of modern hydroacoustic systems, including side sonars, which find numerous applications such as: research of seabed morphology and sediment characteristics, preparation of sea sediment maps, and even in special cases of biocenoses such as sea grass meadows, detection of specific targets at the bottom such as shipwrecks, mines, identification of suitable sites for maritime infrastructure. Such applications require precise information about the position of the objects to be observed. Errors affecting the depiction o

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9

Lee, Dae-Jae. "Acoustic Tracking of Fish Movements in an Artificial Reef Area Using a Split-beam Echo Sounder, Side-scan and Imaging Sonars at Suyeong Man, Busan, Korea." Korean Journal of Fisheries and Aquatic Sciences 46, no. 3 (2013): 273–81. http://dx.doi.org/10.5657/kfas.2013.0273.

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10

Geraga, Maria, Dimitris Christodoulou, Dimitrios Eleftherakis, et al. "Atlas of Shipwrecks in Inner Ionian Sea (Greece): A Remote Sensing Approach." Heritage 3, no. 4 (2020): 1210–36. http://dx.doi.org/10.3390/heritage3040067.

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Underwater cultural heritage (UCH) sites constitute an important part of the overall cultural heritage both nationally and globally as they carry cultural, environmental, scientific, technological, political, economic and social viewpoints. UCH includes not only submerged sites and buildings, but also vessels and aircrafts. The Inner Ionian Sea in Greece is a place rich in a significant number of shipwrecks with a timespan ranging from ancient times right through to the 20th century. The results herein present the study of ancient, World War I (WWI), World War II (WWII) and more recent shipwre

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11

Stanghellini, Giuseppe, Fabrizio Del Bianco, and Luca Gasperini. "OpenSWAP, an Open Architecture, Low Cost Class of Autonomous Surface Vehicles for Geophysical Surveys in the Shallow Water Environment." Remote Sensing 12, no. 16 (2020): 2575. http://dx.doi.org/10.3390/rs12162575.

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OpenSWAP is a class of innovative open architecture, low cost autonomous vehicles for geological/geophysical studies of shallow water environments. Although they can host different types of sensors, these vehicles were specifically designed for geophysical surveys, i.e., for the acquisition of bathymetric and stratigraphic data through single- and multibeam echosounders, side-scan sonars, and seismic-reflection systems. The main characteristic of the OpenSWAP vehicles is their ability of following pre-defined routes with high accuracy under acceptable weather and sea conditions. This would ope

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Kloser, R. J., N. J. Bax, T. Ryan, A. Williams, and B. A. Barker. "Remote sensing of seabed types in the Australian South East Fishery; development and application of normal incident acoustic techniques and associated 'ground truthing'." Marine and Freshwater Research 52, no. 4 (2001): 475. http://dx.doi.org/10.1071/mf99181.

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Calibrated acoustic backscattering measurements using 12, 38 and 120 kHz were collected over depths of 30–230 m, together with benthic epi- and in-fauna, sediments, photographs and video data. Each acoustic ping was envelope detected and digitized by echo sounder to include both the first and second echoes, and specifically designed software removed signal biases. A reference set of distinct habitat types at different depths was established, and a simple classification of the seabed combined both biological and geological attributes. Four seabed types were identified as having broad biological

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13

Castelblanco-Martínez, D. N., M. P. Blanco-Parra, P. Charruau, B. Prezas, I. Zamora-Vilchis, and C. A. Niño-Torres. "Detecting, counting and following the giants of the sea: a review of monitoring methods for aquatic megavertebrates in the Caribbean." Wildlife Research 46, no. 7 (2019): 545. http://dx.doi.org/10.1071/wr19008.

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Abstract The Caribbean is a mega-diverse and bio-geographically important region that consists of the Caribbean Sea, its islands, and surrounding coastlines. Among the billions of aquatic species inhabiting this region, the mega-vertebrates stand out for their social, economic and ecologic relevance. However, the Caribbean has been threatened by climate change, poverty, pollution, environmental degradation and intense growth of the tourism industry, affecting megafauna species directly and indirectly. Population monitoring plays a critical role in an informed conservation process and helps gui

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14

Maccabee, Bruce S., and Charles E. Bell. "Bistatic side scan sonar." Journal of the Acoustical Society of America 92, no. 1 (1992): 626. http://dx.doi.org/10.1121/1.404084.

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15

Lubis, Muhammad Zainuddin, Husnul Kausarian, and Wenang Anurogo. "Seabed Detection Using Application Of Image Side Scan Sonar Instrument (Acoustic Signal)." Journal of Geoscience, Engineering, Environment, and Technology 2, no. 3 (2017): 230. http://dx.doi.org/10.24273/jgeet.2017.2.3.560.

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The importance of knowing the method for seabed detection using side-scan sonar images with sonar instrument is a much-needed requirement right now. This kind of threat also requires frequent sonar surveys in such areas. These survey operations need specific procedures and special equipment to ensure survey correctness. In this paper describes the method of observation and retrieval of marine imagery data using an acoustic signal method, to determine a target based on the sea. Side scan sonar is an instrument consisting of single beam transducer on both sides. Side scan sonar (SSS) is a sonar

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16

Maccabee, Bruce, and Charles E. Bell. "4975887 Bistatic side scan sonar." Deep Sea Research Part B. Oceanographic Literature Review 38, no. 8 (1991): 701–2. http://dx.doi.org/10.1016/s0198-0254(06)80684-9.

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17

Anderson, Aubrey L., and Shufa Dwan. "Simulation of side‐scan sonar." Journal of the Acoustical Society of America 80, S1 (1986): S112. http://dx.doi.org/10.1121/1.2023566.

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18

Daniel, S., F. Le Leannec, C. Roux, B. Soliman, and E. P. Maillard. "Side-scan sonar image matching." IEEE Journal of Oceanic Engineering 23, no. 3 (1998): 245–59. http://dx.doi.org/10.1109/48.701197.

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19

Thorpe, S. A., and A. J. Hall. "Nearshore Side-Scan Sonar Studies." Journal of Atmospheric and Oceanic Technology 10, no. 5 (1993): 778–83. http://dx.doi.org/10.1175/1520-0426(1993)010<0778:nssss>2.0.co;2.

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20

McLarty, Mindy J., Daniel Gonzalez-Socoloske, Anmari Alvarez-Alemán, and Jorge Angulo-Valdés. "Manatee habitat characterization using side-scan sonar." Journal of the Marine Biological Association of the United Kingdom 100, no. 1 (2019): 173–79. http://dx.doi.org/10.1017/s0025315419000973.

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AbstractIdentifying benthic substrates is important to researchers studying aquatic organisms in fresh and salt water systems. Benthic substrates are often not visible from the surface making it necessary to find another method to gather these data. Previous research has demonstrated that low cost side-scan sonar is a reliable way to identify hard substrates, such as rock and gravel, in a small, freshwater stream. In this study, the reliability of the side-scan sonar to accurately identify softer substrates such as grass and mud was tested in a large, brackish lagoon system. A total area of 11

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21

Tan, Kuan Meng, Tien Fu Lu, and Amir Anvar. "Side Scan Sonar Modeling for Maritime Robotic Operations." Applied Mechanics and Materials 152-154 (January 2012): 1195–201. http://dx.doi.org/10.4028/www.scientific.net/amm.152-154.1195.

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One of the key aspects in designing an Autonomous Underwater Vehicle (AUV) simulation framework is sensor modeling. This paper presents specifically the underwater sonar sensor modeling structure used in the proposed AUV simulation framework. This sensor model covers the mathematical aspects from the field of acoustics which mimics real world sensors. Simplified sonar signal models are widely used however rarely discussed in the literature. Based on this designed simulation framework, simple scenario using different sonar configuration is shown and discussed. This paper shows the formulation o

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22

Ge, Qiang, Fengxue Ruan, Baojun Qiao, Qian Zhang, Xianyu Zuo, and Lanxue Dang. "Side-Scan Sonar Image Classification Based on Style Transfer and Pre-Trained Convolutional Neural Networks." Electronics 10, no. 15 (2021): 1823. http://dx.doi.org/10.3390/electronics10151823.

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Side-scan sonar is widely used in underwater rescue and the detection of undersea targets, such as shipwrecks, aircraft crashes, etc. Automatic object classification plays an important role in the rescue process to reduce the workload of staff and subjective errors caused by visual fatigue. However, the application of automatic object classification in side-scan sonar images is still lacking, which is due to a lack of datasets and the small number of image samples containing specific target objects. Secondly, the real data of side-scan sonar images are unbalanced. Therefore, a side-scan sonar

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23

Sternlicht, Daniel D. "Historical development of side scan sonar." Journal of the Acoustical Society of America 141, no. 5 (2017): 4041. http://dx.doi.org/10.1121/1.4989335.

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24

Peng, Lei. "Adaptive De-Noising Approach for Underwater Side Scan Sonar Image." Applied Mechanics and Materials 373-375 (August 2013): 509–12. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.509.

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It is difficult to detect the edges of objects in side scan sonar images due to the complex background, bad contrast and deteriorate edges. Therefore, it is important to remove noise from side scan sonar images. The traditional de-noising methods for optical images may not work well on the sonar image. In this paper, an adaptive de-noising approach is used. The side scan sonar image is first filtered using mean filter to remove the rough noise, then a weighted function is generated using spatial distance filter and intensity distance filter. The parameters are adaptive according to the sonar i

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Efendi, Tria, Dikdik S. Mulyadi, Agung Prasetyo, Amril Amril, Adhi Kusuma, and Agus Iwan Santoso. "Komparasi Pengolahan Data Side Scan Sonar Menggunakan 2 (dua) Perangkat Lunak Triton Imaging Isis dan Sonarwiz (Studi Kasus Perairan Batam Kepulauan Riau)." Jurnal HIDROPILAR 5, no. 1 (2020): 29–34. http://dx.doi.org/10.37875/hidropilar.v5i1.157.

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Survei dan pemetaan laut yang sangat diperlukan dalam berbagai aplikasi kelautan dapat dilakukan dengan berbagai cara, salah satunya dengan proses pencitraan dasar laut. Proses pencitraan dasar laut dapat dilakukan dengan berbagai cara pula, diantaranya pencitraan dengan menggunakan instrumen Side Scan Sonar. Perangkat lunak Triton imaging Isis dan Sonarwiz sebagai perangkat pengolahan data Side Scan Sonar diharapkan dapat memberikan gambaran nyata citra dasar laut sehingga dapat meningkatkan kinerja dari pelaksanaan survei Side Scan Sonar. Tugas Akhir ini akan memberikan penjelasan tentang pe

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Lucchetti, Alessandro, Emilio Notti, Antonello Sala, and Massimo Virgili. "Multipurpose use of side-scan sonar technology for fisheries science." Canadian Journal of Fisheries and Aquatic Sciences 75, no. 10 (2018): 1652–62. http://dx.doi.org/10.1139/cjfas-2017-0359.

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This study illustrates some potential applications of side-scan sonar to explain issues related to fisheries science. Side-scan sonar enabled identification of the footprint of different trawl types. It showed that a twin trawl sweeps a 30% greater area than a traditional trawl and that a semipelagic trawl door has more limited impact than a traditional bottom otter trawl. The side-scan sonar enabled detection and characterization of the interaction of trawl gear with the seafloor. It demonstrated the cod end is floating above the sea bottom during the tow, while the doors and clumps, sweeps a

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Prokhorov, I. V., and A. A. Sushchenko. "Imaging Based on Signal from Side-Scan Sonar." Applied Mechanics and Materials 756 (April 2015): 678–82. http://dx.doi.org/10.4028/www.scientific.net/amm.756.678.

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In this paper authors researched problems about construction of sonar images which based on signal from side-scan sonar. Authors use explicit formula for signal processing. It includes influence of volume scattering in the medium. Moreover, authors use an additional filter for signal. It is logarithm-filtration.

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Bruns, Ines, Peter Holler, Ruggero M. Capperucci, Svenja Papenmeier, and Alexander Bartholomä. "Identifying Trawl Marks in North Sea Sediments." Geosciences 10, no. 11 (2020): 422. http://dx.doi.org/10.3390/geosciences10110422.

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The anthropogenic impact in the German Exclusive Economic Zone (EEZ) is high due to the presence of manifold industries (e.g., wind farms, shipping, and fishery). Therefore, it is of great importance to evaluate the different impacts of such industries, in order to enable reasonable and sustainable decisions on environmental issues (e.g., nature conservation). Bottom trawling has a significant impact on benthic habitats worldwide. Fishing gear penetrates the seabed and the resulting furrows temporarily remain in the sediment known as trawl marks (TM), which can be recognized in the acoustic si

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Service, M., and B. H. Magorrian. "The Extent and Temporal Variation of Disturbance to Epibenthic Communities in Strangford Lough, Northern Ireland." Journal of the Marine Biological Association of the United Kingdom 77, no. 4 (1997): 1151–64. http://dx.doi.org/10.1017/s0025315400038686.

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Side-scan sonar and underwater video were used to determine the impact of a trawl fishery on an epibenthic community associated with the horse mussel, Modiolus modiolus in a Northern Ireland sea lough. The presence of marks caused by trawl otter-boards on the sediments could be clearly seen using side-scan sonar and changes to the epibenthos are described from the video survey. It is apparent from the side-scan sonar survey that changes have occurred in the structure of the superficial sediments on heavily trawled areas. However, there was no clear indication of temporal changes. The utility o

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Joko Rachimzah, Dwi, Eka Djunarsjah, Agung Prasetyo, and Dikdik S Mulyadi. "Pengolahan Data Side Scan Sonar Edgetech 4200 Menggunakan Perangkat Lunak Triton Imaging Studi Kasus Perairan Pulau Kangean Laut Bali." Jurnal HIDROPILAR 2, no. 2 (2016): 111–17. http://dx.doi.org/10.37875/hidropilar.v2i2.47.

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Abstrak - Survei dan pemetaan laut yang sangat diperlukan dalam berbagai aplikasi kelautan dapat dilakukan dengan berbagai cara, salah satunya dengan proses pencitraan dasar laut. Proses pencitraan dasar laut dapat dilakukan dengan berbagai cara pula, diantaranya pencitraan dengan menggunakan instrumen side scan sonar. Adanya perangkat lunak Triton Imaging Isis diharapkan dapat meningkatkan kinerja dari pelaksanaan survei side scan sonar. Tugas Akhir ini akan memberikan penjelasan tentang bagaimanakah pengolahan data Side Scan Sonar dengan menggunakan perangkat lunak Triton Imaging Isis,

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31

Gwon, Dae-Hyeon, Joowan Kim, Moon Hwan Kim, Ho Gyu Park, Tae Yeong Kim, and Ayoung Kim. "Side Scan Sonar based Pose-graph SLAM." Journal of Korea Robotics Society 12, no. 4 (2017): 385–94. http://dx.doi.org/10.7746/jkros.2017.12.4.385.

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32

Johnson, H. Paul, and Maryann Helferty. "The geological interpretation of side-scan sonar." Reviews of Geophysics 28, no. 4 (1990): 357. http://dx.doi.org/10.1029/rg028i004p00357.

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33

Blake, Vanessa S. "The simulation of side-scan sonar images." Archaeological Prospection 2, no. 1 (1995): 29–56. http://dx.doi.org/10.1002/1099-0763(199503)2:1<29::aid-arp6140020105>3.0.co;2-p.

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Mason, D. C., T. P. LeBas, I. Sewell, and C. Angelikaki. "Deblurring of GLORIA side-scan sonar images." Marine Geophysical Researches 14, no. 2 (1992): 125–36. http://dx.doi.org/10.1007/bf01204283.

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35

Lee, Cheol-Ku, Seom-Kyu Jung, and Seong-Ryul Kim. "Distribution of Flood Sediment Deposits using the Seafloor Image by Side Scan Sonar near the Northern Coast of Gungchon-ri, East Sea." Journal of the Korean earth science society 34, no. 1 (2013): 41–50. http://dx.doi.org/10.5467/jkess.2013.34.1.41.

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36

Peng, Lei. "Efficient High-Precision Feature Extraction Method in Side Scan Sonar Image." Applied Mechanics and Materials 678 (October 2014): 197–200. http://dx.doi.org/10.4028/www.scientific.net/amm.678.197.

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Side scan sonar image has disadvantages such as low-resolution, poor image quality, random factors’? disturbance, these disadvantages cause the sonar image less visual perception, poor readability and many other shortcomings. In this paper, geometric correction method and image processing technology were studied, and also a data processing software was developed to improve the side scan sonar data processing from two aspects of data production accuracy and processing efficiency.

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Cuschieri, J. M., and M. Hebert. "Three-Dimensional Map Generation From Side-Scan Sonar Images." Journal of Energy Resources Technology 112, no. 2 (1990): 96–102. http://dx.doi.org/10.1115/1.2905729.

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The generation of three-dimensional (3-D) images and map building are essential components in the development of an autonomous underwater system. Although the direct generation of 3-D images is more efficient than the recovery of 3-D data from 2-D information, at present for underwater applications where sonar is the main form of remote sensing, the generation of 3-D images can only be achieved by either complex sonar systems or with systems which have a rather low resolution. In this paper an overview is presented on the type of sonar systems that are available for underwater remote sensing,

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Kumudham, R., and V. Rajendran. "Side scan sonar image data mapping with geographic reference system." International Journal of Engineering & Technology 7, no. 2.21 (2018): 410. http://dx.doi.org/10.14419/ijet.v7i2.21.12454.

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Many researchers have been done in classifying the surface of the sea floor. Only few concentrated in classifying the sediment layers of the sea floor and the target objects buried. Side Scan Sonar is one such tool, which is used in collecting the images of the seafloor. Sonar equipment transmits a low frequency signal, towards the surface of the seabed for target recognition. It is necessary to locate the area and positioning where the target is located whether it is a ship wreckage or plane crash, mine recognition etc. This paper is proposed to determine the location and position in user fri

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STRIDE, A. H. "The first geological use of side-scan sonar." Geology Today 8, no. 4 (1992): 146–50. http://dx.doi.org/10.1111/j.1365-2451.1992.tb00389.x.

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40

Burguera, Antoni, and Gabriel Oliver. "High-Resolution Underwater Mapping Using Side-Scan Sonar." PLOS ONE 11, no. 1 (2016): e0146396. http://dx.doi.org/10.1371/journal.pone.0146396.

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41

Grothues, Thomas M., Arthur E. Newhall, James F. Lynch, Kaela S. Vogel, and Glen G. Gawarkiewicz. "High-frequency side-scan sonar fish reconnaissance by autonomous underwater vehicles." Canadian Journal of Fisheries and Aquatic Sciences 74, no. 2 (2017): 240–55. http://dx.doi.org/10.1139/cjfas-2015-0301.

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A dichotomy between depth penetration and resolution as a function of sonar frequency, draw resolution, and beam spread challenges fish target classification from sonar. Moving high-frequency sources to depth using autonomous underwater vehicles (AUVs) mitigates this and also co-locates transducers with other AUV-mounted short-range sensors to allow a holistic approach to ecological surveys. This widely available tool with a pedigree for bottom mapping is not commonly applied to fish reconnaissance and requires the development of an interpretation of pelagic reflective features, revisitation o

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Lubis, Muhammad Zainuddin, Wenang Anurogo, Hanah Khoirunnisa, Sudra Irawan, Oktavianto Gustin, and Arif Roziqin. "Using Side-Scan Sonar instrument to Characterize and map of seabed identification target in punggur sea of the Riau Islands, Indonesia." Journal of Geoscience, Engineering, Environment, and Technology 2, no. 1 (2017): 1. http://dx.doi.org/10.24273/jgeet.2017.2.1.11.

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Punggur sea has many habitats, object, and structured of seabed with hight tide and wave. Side scan sonar is an underwater acoustic instrument for identification of seabed. This research aims to classify types of seabed and measure seabed identification into the sea water with grain size (dB), location, altitude (m) and target using side scan sonar instrument. This research also uses one types of side scan sonar in one places with 3 line of collecting data to get more variant seabed. Side scan sonar data of 20 km of side-scan sonar profiling (CM2, C-MAX Ltd, UK) with altitude max 20 m and a wo

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Fish, J. P., and M. Klein. "The Use of Reconnaissance Hydrographic Surveys for Establishment of Essential Navigation Bathymetric Data in the Third World Countries." Canadian Surveyor 39, no. 2 (1985): 143–45. http://dx.doi.org/10.1139/tcs-1985-0018.

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Many third world countries do not have the resources to conduct classic hydrographic surveys, either due to the length of the coastline or the level of available funds. In the past, this has resulted in an arbitrary choice of navigational channel areas to be surveyed. In order to more effectively utilize the limited resources available in third world countries, the use of a large footprint side scan sonar to provide reconnaissance type information to the surveyor is advocated so that the surveyor may “triage” the large areas to be surveyed and survey only areas which offer the highest return f

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Zhao, Kun, Jisheng Ding, YanFei Sun, and ZhiYuan Hu. "Side-scan Sonar Image De-noising Based on Bidimensional Empirical Mode Decomposition and Non-local Means." E3S Web of Conferences 206 (2020): 03019. http://dx.doi.org/10.1051/e3sconf/202020603019.

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In order to suppress the multiplicative specular noise in side-scan sonar images, a denoising method combining bidimensional empirical mode decomposition and non-local means algorithm is proposed. First, the sonar image is decomposed into intrinsic mode functions(IMF) and residual component, then the high frequency IMF is denoised by non-local mean filtering method, and finally the processed intrinsic mode functions and residual component are reconstructed to obtain the de-noised side-scan sonar image. The paper’s method is compared with the conventional filtering algorithm for experimental qu

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Lubis, Muhammad Zainuddin, Kasih Anggraini, Husnul Kausarian, and Sri Pujiyati. "Review: Marine Seismic And Side-Scan Sonar Investigations For Seabed Identification With Sonar System." Journal of Geoscience, Engineering, Environment, and Technology 2, no. 2 (2017): 166. http://dx.doi.org/10.24273/jgeet.2017.2.2.253.

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Marine seismic reflection data have been collected for decades and since the mid-to late- 1980s much of this data is positioned relatively accurately. Marine geophysical acquisition of data is a very expensive process with the rates regularly ship through dozens of thousands of euros per day. Acquisition of seismic profiles has the position is determined by a DGPS system and navigation is performed by Hypack and Maxview software that also gives all the offsets for the equipment employed in the survey. Examples of some projects will be described in terms of the project goals and the geophysical

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Tao, Weiliang, Yan Liu, and Wenbin Hu. "Inversion of Side Scan Sonar Motion and Posture in Seabed Geomorphology." Polish Maritime Research 24, s2 (2017): 81–88. http://dx.doi.org/10.1515/pomr-2017-0068.

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Abstract Side scan sonar measurement platform, affected by underwater environment and its own motion precision, inevitably has posture and motion disturbance, which greatly affects accuracy of geomorphic image formation. It is difficult to sensitively and accurately capture these underwater disturbances by relying on auxiliary navigation devices. In this paper, we propose a method to invert motion and posture information of the measurement platform by using the matching relation between the strip images. The inversion algorithm is the key link in the image mosaic frame of side scan sonar, and

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Dura, E., J. Bell, and D. Lane. "Reconstruction of textured seafloors from side-scan sonar images." IEE Proceedings - Radar, Sonar and Navigation 151, no. 2 (2004): 114. http://dx.doi.org/10.1049/ip-rsn:20040262.

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Coiras, Enrique, Yvan Petillot, and David M. Lane. "Multiresolution 3-D Reconstruction From Side-Scan Sonar Images." IEEE Transactions on Image Processing 16, no. 2 (2007): 382–90. http://dx.doi.org/10.1109/tip.2006.888337.

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Zhou, Yan, Qingwu Li, and Guanying Huo. "Automatic Side-Scan Sonar Image Enhancement in Curvelet Transform Domain." Mathematical Problems in Engineering 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/493142.

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We propose a novel automatic side-scan sonar image enhancement algorithm based on curvelet transform. The proposed algorithm uses the curvelet transform to construct a multichannel enhancement structure based on human visual system (HVS) and adopts a new adaptive nonlinear mapping scheme to modify the curvelet transform coefficients in each channel independently and automatically. Firstly, the noisy and low-contrast sonar image is decomposed into a low frequency channel and a series of high frequency channels by using curvelet transform. Secondly, a new nonlinear mapping scheme, which coincide

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Lubis, Muhammad Zainuddin, Rasyid Alkhoir Lubis, and Ramadhan Ulil Albab Lubis. "The Two-Dimensional Wavelet Transform De-noising and Combining with Side Scan Sonar Image." Journal of Applied Geospatial Information 1, no. 01 (2017): 1–4. http://dx.doi.org/10.30871/jagi.v1i01.307.

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This paper puts forward an image de-noising method based on 2D wavelet transform with the application of the method in seabed identification data collection system. Two-dimensional haar wavelets in image processing presents a unified framework for wavelet image compression and combining with side scan sonar image. Seabed identification target have 7 target detection in side scan sonar imagery result. The vibration signals were analyzed to perform fault diagnosis. The obtained signal was time-domain signal. The experiment result shows that the application of 2D wavelet transform image de-noisin

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