2015 XVI Workshop on Information Processing and Control (RPIC) 2015
DOI: 10.1109/rpic.2015.7497071
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OS-CFAR process in 2-D for object segmentation from Sidescan Sonar data

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Cited by 12 publications
(5 citation statements)
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“…In terms of classical theory, the CFAR method is often combined with a variety of distribution models (k distribution, Weibull distribution, normal distribution, GP distribution) and applied in the underwater acoustic signal beamforming and target automatic detection [106,107]. Shen designed a special CFAR detector using the reverberation properties of the ocean [108,109]. It could analyze the active sonar echo and fit the data efficiently.…”
Section: Methodmentioning
confidence: 99%
“…In terms of classical theory, the CFAR method is often combined with a variety of distribution models (k distribution, Weibull distribution, normal distribution, GP distribution) and applied in the underwater acoustic signal beamforming and target automatic detection [106,107]. Shen designed a special CFAR detector using the reverberation properties of the ocean [108,109]. It could analyze the active sonar echo and fit the data efficiently.…”
Section: Methodmentioning
confidence: 99%
“…In the past decades, the traditional underwater target detection methods are mainly used for sonar image analysis. These methods include detection based on pixel characteristics, gray value or the prior knowledge of the target [1][2][3][4][5][6]. Due to the complexity of underwater environment, the quality of sonar image is seriously affected by its own noise, reverberation and environmental noise, resulting in low image resolution, unclear edge details, and significant speckle noise.…”
Section: Introductionmentioning
confidence: 99%
“…Then, Sebastiá n A. [13] applied order statistic-CFAR (OS-CFAR) technology to target segmentation of sonar images, which has good performance on high-resolution SSS images but is constrained by the image signal-to-noise ratio. According to the current research, the current researchers are all studying the moving target detection on the high-resolution sonar images.…”
Section: Introductionmentioning
confidence: 99%