Recognition of Cold-Water Corals in Synthetic Aperture Sonar Imagery

Sture, Øystein; Ludvigsen, Martin; Scheide, Margrete S.; Thorsnes, Terje

doi:10.1109/auv.2018.8729718

Cited by 8 publications

(7 citation statements)

References 34 publications

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“…To record sonar imagery, a Kongsberg HiSAS 1030 synthetic aperture sonar system (Kongsberg Maritime AS, Kongsberg, Norway) was deployed on a HUGIN 1000 AUV. As opposed to regular side-scanning sonar systems, SAS systems utilize more than a single ping to reconstruct a given location in the output imagery, which improves spatial resolution both across-and along-track (Hansen et al, 2004;Sture et al, 2018). Using the SASequipped HUGIN AUV, the northwestern region of the Tautra Ridge was surveyed in a systematic lawnmower pattern at a mean seafloor altitude of 26 m. The resulting imagery was postprocessed in Kongsberg Maritime's "Reflection" software, and ultimately georeferenced at a pixel resolution of 4 cm x 4 cm.…”

Section: Sas Datamentioning

confidence: 99%

“…The HUGIN AUV was equipped with a synthetic aperture sonar (SAS), and the recorded sonar imagery clearly revealed the presence of cauliflower-patterned reef structures (Ludvigsen et al, 2014). Sture et al (2018) later demonstrated that these D. pertusum reefs could be accurately identified in SAS imagery by applying a convolutional neural network (CNN) classification algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…During the survey, D. pertusum was optically confirmed to be present, but the resulting data were not analyzed extensively. More recently, ROV-acquired video from the Tautra Ridge was used to verify coral presence in acoustic SAS imagery (Sture et al, 2018). Here, the optical information served as a useful qualitative guide, but the video data were not assessed quantitatively.…”

Section: Introductionmentioning

confidence: 99%

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Remote Sensing of the Tautra Ridge: An Overview of the World’s Shallowest Cold-Water Coral Reefs

et al. 2022

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On the Tautra Ridge – a 39-100 m deep morainic sill located in the middle of the Trondheimsfjord, Norway – some of the world’s shallowest known occurrences of the scleractinian cold-water coral (CWC) Desmophyllum pertusum can be found. The earliest D. pertusum records from the Tautra Ridge date back to the 18th century, and since then, the location has provided easy access to physical coral specimens for numerous scientific studies. In 2013, the ridge was declared a marine protected area by the Norwegian Government due to its unique CWC reefs. However, few attempts have to our knowledge yet been made to characterize the distribution, extent and condition of these reefs extensively. The aim of the current study was therefore to add geospatial context to the Tautra CWC reef complex. In the study, data from multibeam echo sounding, synthetic aperture sonar imaging and underwater hyperspectral imaging are used to assess CWC reef occurrences from multiple perspectives. The study demonstrates how complementary remote sensing techniques can be used to increase knowledge generation during seafloor mapping efforts. Ultimately, predictive modeling based on seafloor geomorphometry is used to estimate both distribution and areal coverage of D. pertusum reefs along the majority of the Tautra Ridge. Our findings suggest that D. pertusum reef distribution on the Tautra Ridge is affected by several geomorphometric seafloor properties, and that the total reef extent in the area likely is close to 0.64 km2. Better description of current patterns across the Tautra Ridge will improve our understanding of the interaction between hydrography and geomorphology at the Tautra CWC reef complex in the future.

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Section: Sas Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Remote Sensing of the Tautra Ridge: An Overview of the World’s Shallowest Cold-Water Coral Reefs

et al. 2022

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“…Nevertheless, for the deep-sea, passive hyperspectral remote sensing is no longer applicable. Current methods at disposal for obtaining descriptions of seafloor benthic habitats and organisms are sonar surveying, underwater photography, and grab or trawl sampling [ 78 , 79 , 80 ]. Sonar surveying is more concerned with the topographical features of benthic habitats.…”

Section: Applications Of Underwater Hyperspectral Imaging Technolomentioning

confidence: 99%

Underwater Hyperspectral Imaging Technology and Its Applications for Detecting and Mapping the Seafloor: A Review

Liu

Men

et al. 2020

Sensors

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Common methods of ocean remote sensing and seafloor surveying are mainly carried out by airborne and spaceborne hyperspectral imagers. However, the water column hinders the propagation of sunlight to deeper areas, thus limiting the scope of observation. As an emerging technology, underwater hyperspectral imaging (UHI) is an extension of hyperspectral imaging technology in air conditions, and is undergoing rapid development for applications in shallow and deep-sea environments. It is a close-range, high-resolution approach for detecting and mapping the seafloor. In this paper, we focus on the concepts of UHI technology, covering imaging systems and the correction methods of eliminating the water column’s influence. The current applications of UHI, such as deep-sea mineral exploration, benthic habitat mapping, and underwater archaeology, are highlighted to show the potential of this technology. This review can provide an introduction and overview for those working in the field and offer a reference for those searching for literature on UHI technology.

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“…A variety of algorithms exist for forming images from SAS acoustic measurements [3]- [6]. These reconstruction algorithms aim to produce high quality imagery to support underwater visualization tasks including target localization [7], monitoring man-made infrastructure [8], and studying underwater ecologies [9].…”

Section: Introductionmentioning

confidence: 99%

SINR: Deconvolving Circular SAS Images Using Implicit Neural Representations

Reed¹,

Blanford²,

Brown³

et al. 2022

Preprint

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Circular Synthetic aperture sonars (CSAS) capture multiple observations of a scene to reconstruct high-resolution images. We can characterize resolution by modeling CSAS imaging as the convolution between a scene's underlying point scattering distribution and a system-dependent point spread function (PSF). The PSF is a function of the transmitted waveform's bandwidth and determines a fixed degree of blurring on reconstructed imagery. In theory, deconvolution overcomes bandwidth limitations by reversing the PSF-induced blur and recovering the scene's scattering distribution. However, deconvolution is an illposed inverse problem and sensitive to noise. We propose a selfsupervised pipeline (does not require training data) that leverages an implicit neural representation (INR) for deconvolving CSAS images. We highlight the performance of our SAS INR pipeline, which we call SINR, by implementing and comparing to existing deconvolution methods. Additionally, prior SAS deconvolution methods assume a spatially-invariant PSF, which we demonstrate yields subpar performance in practice. We provide theory and methods to account for a spatially-varying CSAS PSF, and demonstrate that doing so enables SINR to achieve superior deconvolution performance on simulated and real acoustic SAS data. We provide code 1 to encourage reproducibility of research.

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Recognition of Cold-Water Corals in Synthetic Aperture Sonar Imagery

Cited by 8 publications

References 34 publications

Remote Sensing of the Tautra Ridge: An Overview of the World’s Shallowest Cold-Water Coral Reefs

Remote Sensing of the Tautra Ridge: An Overview of the World’s Shallowest Cold-Water Coral Reefs

Underwater Hyperspectral Imaging Technology and Its Applications for Detecting and Mapping the Seafloor: A Review

SINR: Deconvolving Circular SAS Images Using Implicit Neural Representations

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