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1.	Al-Rawi, Mohammed, et al. (author) Algorithms for the Detection of First Bottom Returns and Objects in the Water Column in Side-Scan Sonar Images 2017 In: OCEANS '17 A Vision for our Marine Future OCEANS '17. - Aberdeen, United Kingdom. - 9781509052783 Conference paper (peer-reviewed)abstract Underwater imaging has become an active research area in recent years as an effect of increased interest in underwater environments and is getting potential impact on the world economy, in what is called blue growth. Since sound propagates larger distances than electromagnetic waves underwater, sonar is typically used for underwater imaging. One interesting sonar image setting is comprised of using two parts (left and right) and is usually referred to as sidescan sonar. The image resulted from sidescan sonars, which is called waterfall image, usually has to distinctive parts, the water column and the image seabed. Therefore, the edge separating these two parts, which is called the first bottom return, is the real distance between the sonar and the seabed bottom (which is equivalent to sensor primary altitude). The sensory primary altitude can be measured if the imaging sonar is complemented by interferometric sonar, however, simple sonar systems have no way to measure the first bottom returns other than signal processing techniques. In this work, we propose two methods to detect the first bottom returns; the first is based on smoothing cubic spline regression and the second is based on a moving average filter to detect signal variations. The results of both methods are compared to the sensor primary altitude and have been successful in 22 images out of 25.

Al-Rawi, Mohammed, et al. (author)
Algorithms for the Detection of First Bottom Returns and Objects in the Water Column in Side-Scan Sonar Images
2017
In: OCEANS '17 A Vision for our Marine Future OCEANS '17. - Aberdeen, United Kingdom. - 9781509052783
Conference paper (peer-reviewed)abstract
- Underwater imaging has become an active research area in recent years as an effect of increased interest in underwater environments and is getting potential impact on the world economy, in what is called blue growth. Since sound propagates larger distances than electromagnetic waves underwater, sonar is typically used for underwater imaging. One interesting sonar image setting is comprised of using two parts (left and right) and is usually referred to as sidescan sonar. The image resulted from sidescan sonars, which is called waterfall image, usually has to distinctive parts, the water column and the image seabed. Therefore, the edge separating these two parts, which is called the first bottom return, is the real distance between the sonar and the seabed bottom (which is equivalent to sensor primary altitude). The sensory primary altitude can be measured if the imaging sonar is complemented by interferometric sonar, however, simple sonar systems have no way to measure the first bottom returns other than signal processing techniques. In this work, we propose two methods to detect the first bottom returns; the first is based on smoothing cubic spline regression and the second is based on a moving average filter to detect signal variations. The results of both methods are compared to the sensor primary altitude and have been successful in 22 images out of 25.

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