nondestructive methods for recovering the spatial- temporal structure of ocean surface waves &...
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Nondestructive Methods for Recovering the Spatial-Temporal Structure of Ocean Surface Waves
&Seeing Through Waves
Nondestructive Methods for Recovering the Spatial-Temporal Structure of Ocean Surface Waves
&Seeing Through Waves
Howard Schultz <[email protected]>Chris J. Zappa, Michael L. Banner, Larry Pezzaniti
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?– 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
• A bundle of light rays is characterized by intensity, a frequency distribution (color), and a polarization distribution
• Polarization distribution is characterized by Stokes parametersS = (S0, S1, S2, S3)
• The change in polarization on reflection or scattering is governed by Muller Calculus
SOUT = M SIN
• 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 polarimetry?
Amount of circular polarizationOrientation and degree of linear polarizationIntensity
Incident LightMuller MatrixScattered Light
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
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∂z /∂x and ∂z /∂y
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
Slope in Degrees
X-Component
Y-Component
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 initiativehttp://www.opl.ucsb.edu/radyo/
Motorized Stage12mm travel5mm/sec max speed
ObjectiveAssembly
Polarizing beamsplitterassembly
Camera 1(fixed)
Camera 2
Camera 3Camera 4
FLIP INSTRUMENTATION SETUP
Scanning Altimeters
Infrared Camera
Air-Sea Flux Package
Polarimeter
Visible Camera
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
Reconstructed Surface Video
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 FormationSubsurface-to-surface
Imaging Array
Exposure Center
Observation RaysAir
Water
Image Formationsurface-to-subsurface
Imaging Array
Exposure Center
Air
Water
Imaging Array
Exposure Center
Optical Flattening Algorithm
• 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-distortionA lens maps incidence angle θ to image position X
Lens
Imaging Array
X
θ
X
θ
Lens
Imaging Array
Un-distortionA lens maps incidence angle θ to image position X
X
Lens
Imaging Array
Un-distortionA lens maps incidence angle θ to image position X
X
θ
Lens
Imaging Array
Un-distortionA lens maps incidence angle θ to image position X
X
θ
Lens
Imaging Array
Un-distortionA lens maps incidence angle θ to image position X
Distorted Image Point
Image array
Un-distortionUse the refraction angle to “straighten out” light
rays
Air
Water
Air
Water
Distorted Image PointUn-distorted Image Point
Image array
Un-distortionUse the refraction angle to “straighten out” light
rays
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 contactHoward SchultzUniversity of MassachusettsDepartment of Computer Science140 Governors DriveAmherst, MA 01003Phone: 413-545-3482Email: [email protected]