|
Descripción
|
|
|---|---|
| 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, sonar imaging outperforms optical imaging underwater. 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 (i.e. sensor primary altitude). The sensory primary altitude can be measured if the 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 proposed two methods to detect the first bottom returns; the first is based on 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. | |
|
Internacional
|
Si |
|
ISSN o ISBN
|
10.1109/OCEANSE.2017.8084587 |
|
Entidad relacionada
|
Oceans' 17 Marine Technology Society (MTS)/ IEEE Oceanic Engineering Society (OES) |
|
Nacionalidad Entidad
|
REINO UNIDO |
|
Lugar del congreso
|
Aberdeen, Scotland |