The impact of digital image configuration on submarine periscope operator workload, situation awareness, meta-awareness and performance

Michailovs, Steph; Howard, Zachary L; Pond, Stephen; Visser, Troy A. W.; Bell, Jason; Pinniger, Gavin J.; Irons, Jessica; Schmitt, Megan; Fitzgerald, Madison; Stoker, Matthew; Carter, Owen; Huf, Sam; Loft, Shayne

doi:10.1016/j.cogsys.2022.09.001

Cited by 5 publications

(1 citation statement)

References 31 publications

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“…The research focus of the optical detection is to reduce the impact of the strong scattering effect and fast absorption power attenuation characteristics of the water medium on underwater communication, imaging, and detection [73]. As shown in figure 11, there are three main optical detection methods for seafloor targets, synchronous scanning imaging, range gating imaging, and underwater Lidar imaging [74].…”

Section: Optical Detectionmentioning

confidence: 99%

Sonar image intelligent processing in seabed pipeline detection: review and application

Shi,

Cao,

et al. 2024

Meas. Sci. Technol.

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Subsea pipelines rely primarily on imaging sonar for detection and identification. We analyze the imaging principles of side scan sonar, multi-beam sonar, synthetic aperture sonar, seafloor penetrating sonar and forward-looking sonar. We discuss their effectiveness in detecting seabed pipelines, as well as their limitations in image recognition capabilities. As intelligent algorithms have become increasingly important in the field of image processing, we review the sonar image intelligent detection and recognition algorithms in the past six years and summarize the internal principles and application effects of classic algorithms such as SIFT (Scale-Invariant Feature Transform), KMA (K-means algorithm), and CFAR (Constant False-Alarm Rate) that currently show good application prospects. Simultaneously, we review the particular strengths exhibited by these algorithms, such as contour feature extraction, image segmentation and clustering, target recognition under background noise, etc. The research on intelligent processing of sonar images opens up a new way to solve the difficult problem of the seabed targets detection and recognition.

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Section: Optical Detectionmentioning

confidence: 99%