Final Program - Oceans 2007 MTS/IEEE Vancouver

Tutorials (cont’d.)
fi rst, since they relate to the principles of image
classifi cation. Near nadir, the amplitudes and
shapes of sounder echoes are rich in sediment
information. Away from vertical incidence, echoes
carry sediment information in their amplitudes and
their noise characteristics, but not in their shapes.
Echoes from imaging sonars, with their wide
horizontal beamwidths, become rasters in sonar
images, so noise in these echoes becomes image
texture. Macro-roughness such as sand waves and
changes in sediment also contribute to texture.
Image amplitude and texture are both heavily
infl uenced by sediment type and are exploited for
segmentation.
Sonar calibration is not necessary for image-based
acoustic classifi cation. Image amplitudes are
made consistent throughout a survey, but remain
in relative, not absolute, units. Since calibrating
imaging sonars is challenging, the ability to use
systems that need only be consistent offers costeffective
practical classifi cation for military and
civil purposes.
Topics in this tutorial include:
Quality control, suppressing system artifacts.
Compensating images for beam patterns and
grazing angle effects.
Features that capture amplitude and texture
characteristics.
Classifi cation with amplitude: backscatter, backscatter
vs. grazing angle.
Classifi cation with texture: Pace, Haralick,
fractal, wavelet.
Differences between classifying multibeam and
sidescan images: resolution, using bathymetric
data for compensation, benefi ts of images
stitched together from backscatter in beams.
Supervised classifi cation, training sets.
Unsupervised classifi cation, PCA, manual and
automated clustering.
Using non-acoustic data to relate acoustic
classes to sediment geoacoustic properties.
Categorical interpolation.
Maps with acoustic classes in similarity colours.
The techniques presented in this tutorial are wide
ranging, and do not concentrate on a selected
technical approach. Participants in this tutorial
can expect to gain a thorough understanding of
the principles and practice of image-based sediment
classifi cation.
Meeting Room 18
T3 – Signal Processing Methods for Underwater
Acoustic Communications
By Dr. Milica Stojanovic, MS, PhD – Principal
Scientist at the Massacheusetts Institute of
Technology & Guest Investigator at the Woods
Hole Oceanographic Institution Lee Freitag,
BS, MS – Senior Engineer at Woods Hole
Oceanographic Institution
Wireless information transmission through the
ocean is one of the enabling technologies for
the development of future ocean-observation
systems, whose applications include gathering
of scientifi c data, pollution control, climate
recording, detection of objects on the ocean
fl oor, and transmission of images from remote
sites. Implicitly, wireless signal transmission is crucial
for control of autonomous underwater vehicles
(AUVs) which will serve as mobile nodes in the
future information networks of distributed underwater
sensors. Wireless communication provides
advantages of collecting data without the need
to retrieve instruments, and maneuvering underwater
vehicles and robots without the burden
of cables.
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