Transcript PolarimetryBriefingx

Nondestructive Methods for Recovering the SpatialTemporal Structure of Ocean Surface Waves
&
Seeing Through Waves
Howard Schultz <[email protected]>
Chris J. Zappa, Michael L. Banner, Larry Pezzaniti
August 2010
Outline
• Why recover the 2-D spatial-temporal structure of the
ocean surface?
• Requirements
• Why use a passive optical technique
• What is polarimetry?
• What is the Polarimetric Slope Sensing (PSS) technique?
• Build and Test an Imaging Polarimeter for Ocean Apps.
• Recent Experiment and Results
• Optical Flattening
• Seeing Through Waves
• Why recover the 2-D structure of the ocean surface?
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Characterize small scale wave dynamics
Air-sea interactions occur at short wavelengths
Non-linear interaction studies require phase-resolved surface topography
Enable through-the-wave imaging
• Requirements
– Spatial resolution (resolve capillary waves) ~ 1mm
– Temporal resolution ~60Hz sampling rate
– Shutter speed < 1 msec
• Why use a passive optical technique
– Probes disturb the air-sea interaction
– Radar do not produce phase-resolved surfaces
– Active techniques are complex and expensive
What is polarimetry?
• Light has 3 basic qualities
• Color, intensity and polarization
• Humans do not see polarization
Linear Polarization
http://www.enzim.hu/~szia/cddemo/edemo0.htm
Circular Polarization
What is polarimetry?
•
A bundle of light rays is characterized by intensity, a frequency distribution
(color), and a polarization distribution
•
Polarization distribution is characterized by Stokes parameters
S = (S0, S1, S2, S3)
Amount of circular polarization
Orientation and degree of linear polarization
Intensity
•
The change in polarization on reflection or scattering is governed by Muller
Calculus
SOUT = M SIN
Incident Light
Muller Matrix
Scattered Light
•
Where M contains information about the shape and material properties of
the scattering media
•
The goal: Measure SOUT and SIN and infer the parameters of M
What is the Polarimetric Slope
Sensing (PSS) technique?
• Use the change in polarization of reflected
skylight to infer the 2D surface slope for
every pixel in the imaging polarimeter’s
field-of-view
What is the Polarimetric Slope
Sensing (PSS) technique?
How well does the PSS technique work?
• Conduct a feasibility study
– Rented a linear imaging polarimeter
– Laboratory experiment
• setup a small 1m x 1m wavetank
• Used unpolarized light
• Used wire gauge to simultaneously measure wave profile
– Field experiment
• Collected data from a boat dock
• Overcast sky (unpolarized)
• Used a laser slope gauge
Looking at 90 to the waves
Looking at 45 to the waves
Looking at 0 to the waves
X-Component
Y-Component
Slope in Degrees
X-Component
Y-Component
Slope in Degrees
Build and Test an Imaging Polarimeter
for Oceanographic Applications
– Funded by an ONR DURIP
– Frame rate 60 Hz
– Shutter speed as short as 10 μsec
– Measure all Stokes parameters
– Rugged and light weight
– Deploy in the Radiance in a Dynamic
Ocean (RaDyO) research initiative
http://www.opl.ucsb.edu/radyo/
Camera 3
Camera 4
Camera 1
(fixed)
Polarizing
beamsplitter
assembly
Objective
Assembly
Camera 2
Motorized Stage
12mm travel
5mm/sec max speed
FLIP INSTRUMENTATION SETUP
Scanning Altimeters
Visible Camera
Infrared Camera
Polarimeter
Air-Sea Flux Package
Sample Results
• A sample dataset from the Santa Barbara Channel
experiment was analyzed
• Video 1 shows the x- and y-slope arrays for 1100 frames
• Video 2 shows the recovered surface (made by
integrating the slopes) for the first 500 frames
• A statistical comparison between our results and
published results is given as well
X and Y Slope Video
Show the video
http://vis-www.cs.umass.edu/~hschultz/WaveTank/2008_Run42_XandYSlopes_Cam4_Frames8891-10152_w_trailer-1.wmv
Reconstructed Surface Video
Show the video
http://vis-www.cs.umass.edu/~hschultz/WaveTank/Z_movie.mpg
Preliminary Polarimeter Comparison with Cox and Munk
Seeing Through Waves
• Sub-surface to surface imaging
• Surface to sub-surface imaging
Optical Flattening
Optical Flattening
• Remove the optic distortion caused by
surface waves to make it appear as if the
ocean surface was flat
– Use the 2D surface slope field to find the
refracted direction for each image pixel
– Refraction provides sufficient information to
compensate for surface wave distortion
– Real-time processing
Image Formation
Subsurface-to-surface
Air
Observation Rays
Water
Imaging Array
Exposure Center
Image Formation
surface-to-subsurface
Exposure Center
Imaging Array
Air
Water
Imaging Array
Exposure Center
Optical Flattening Algorithm
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Collect polarimetric images
Compute the Stokes parameters for each pixel
Recover the 2D surface slope field
Compute the refraction for each rays as it
passes through the air-sea interface
• Create an undistorted image
Un-distortion
A lens maps incidence angle θ to image position X
θ
Lens
Imaging Array
X
Un-distortion
A lens maps incidence angle θ to image position X
θ
Lens
Imaging Array
X
Un-distortion
A lens maps incidence angle θ to image position X
Lens
Imaging Array
X
Un-distortion
A lens maps incidence angle θ to image position X
θ
Lens
Imaging Array
X
Un-distortion
A lens maps incidence angle θ to image position X
θ
Lens
Imaging Array
X
Un-distortion
Use the refraction angle to “straighten out” light rays
Distorted Image Point
Image array
Air
Water
Un-distortion
Use the refraction angle to “straighten out” light rays
Un-distorted Image Point
Distorted Image Point
Image array
Air
Water
Real-time Un-Distortion
• The following steps are taken
Real-time
Capable
– Collect Polarimetric Images

– Convert to Stokes Parameters

– Compute Slopes (Muller Calculus) 
– Refract Rays (Lookup Table)

– Remap Rays to Correct Pixel

Detecting Submerged Objects
“Lucky Imaging”
• Use refraction information to keep track of where
each pixel (in each video frame) was looking in
the water column
• Build up a unified view of the underwater
environment over several video frames
• Save rays that refract toward the target area
• Reject rays that refract away from the target
area
For more information contact
Howard Schultz
University of Massachusetts
Department of Computer Science
140 Governors Drive
Amherst, MA 01003
Phone: 413-545-3482
Email: [email protected]