Shape-from-Polarimetry: A New Tool for Studying the Air-Sea Interface
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Transcript of Shape-from-Polarimetry: A New Tool for Studying the Air-Sea Interface
Shape-from-Polarimetry:A New Tool for Studying the Air-Sea Interface
Howard Schultz, UMass Amherst, Dept of Computer ScienceChris J. Zappa, Michael L. Banner, Russel Morison, Larry Pezzaniti
Introduction
• What is Polarimetry– Light has 3 basic qualities– Color, intensity and polarization– Humans do not see polarization
Introduction
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 scattering is described 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
Muller Calculus
Amount of circular polarizationOrientation and degree of linear polarizationIntensity
Incident LightMuller MatrixScattered Light
Shape-from-Polarimetry (SFP)
• Use the change in polarization of reflected or refracted 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
Shape-from-Polarimetry
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RAW =
α +η α −η 0 0α −η α +η 0 0
0 0 γ Re 00 0 0 γ Re
⎡
⎣
⎢ ⎢ ⎢ ⎢
⎤
⎦
⎥ ⎥ ⎥ ⎥
and TWA =
′ α + ′ η ′ α − ′ η 0 0′ α − ′ η ′ α + ′ η 0 00 0 ′ γ Re 00 0 0 ′ γ Re
⎡
⎣
⎢ ⎢ ⎢ ⎢
⎤
⎦
⎥ ⎥ ⎥ ⎥
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α =12
tan θ i −θ t( )tan θ i +θ t( )
⎡
⎣ ⎢
⎤
⎦ ⎥2
η =12
sin θ i −θ t( )sin θ i +θ t( )
⎡
⎣ ⎢
⎤
⎦ ⎥2
γRe =tan θ i −θ t( ) sin θ i −θ t( )tan θ i +θ t( ) sin θ i +θ t( )
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′ α =12
2sin ′ θ i( ) sin ′ θ t( )sin ′ θ i + ′ θ t( ) cos ′ θ i + ′ θ t( )
⎡
⎣ ⎢
⎤
⎦ ⎥2
′ η =12
2sin ′ θ i( ) sin ′ θ t( )sin ′ θ i + ′ θ t( )
⎡
⎣ ⎢
⎤
⎦ ⎥2
′ γ Re =4 sin2 ′ θ i( ) sin2 ′ θ t( )
sin2 ′ θ i + ′ θ t( ) cos2 ′ θ i + ′ θ t( )
S = SAW + SWA
SAW = RAWSSKY and SWA = TAWSUP
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sin θ i( ) = n sin θ t( ) and sin ′ θ i( ) =1n
sin ′ θ t( )
Kattawar, G. W., and C. N. Adams (1989), “Stokes vector calculations of the submarine light-field in an atmosphere-ocean with scattering according to a Rayleigh phase matrix - Effect of interface refractive-index on radiance and polarization,” Limnol. Oceanogr., 34(8),1453-1472.
Shape-from-Polarimetry
• For simplicity we incorporated 3 simplifying assumptions– Skylight is unpolarized SSKY = SSKY(1,0,0,0) good for overcast days– In deep, clear water upwelling light can be neglected SWA =
(0,0,0,0). – The surface is smooth within the pixel field-of-view
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DOLP θ( ) =S1
2 + S22
S02 and φ =
12
tan−1 S2
S1
⎛ ⎝ ⎜
⎞ ⎠ ⎟+ 90°
Shape-from-Polarimetry
Sensitivity = (DOLP) / θ
Experiments
• 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 wavesLooking at 45 to the wavesLooking at 0 to the waves
Slope in Degrees
X-Component
Y-Component
X-Component Y-Component
Slope in Degrees
Build an Imaging Polarimeter for Oceanographic Applications – Polaris Sensor Technologies
– 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
Air-Sea Flux Package
Imaging Polarimeter
Scanning Altimeters and Visible Camera
~36°
Deployed during the ONR experimentRadiance in a Dynamic Ocean (RaDyO)
Analysis & Conclusion
• 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
Time series comparison
Convert slope arrays to a height array
Convert slope arrays to a height array (Integration)
Convert slope arrays to a height array
Use the Fourier derivative theorem
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sX =∂h∂x
, sY =∂h∂y
ˆ s X = F sX( ), ˆ s Y = F sY( )
ikXˆ h = ˆ s X , iky
ˆ h = ˆ s Y
ˆ h =−ikX ˆ s X − ikY ˆ s Y
k 2
h = F −1 ˆ h ( )
Reconstructed Surface Video
Analysis & Conclusion
• The shape-from-polarimetry method works well for small waves in the 1mm to 10cm range.
• Need to improve the theory by removing the three simplifying assumptions– Skylight is unpolarized SSKY = SSKY(1,0,0,0)– Upwelling light can be neglected SWA = (0,0,0,0). – The surface is smooth within the pixel field-of-view
• Needs to have an independent estimate of lower frequency waves.
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
Seeing Through Waves
0 20 40 60 80 0 10 20 30 40
Seeing Through Waves
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
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
Un-distorted Image Point
Image array
Un-distortionUse the refraction angle to “straighten out” light rays
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 ✔
Image Formationsurface-to-subsurface
Imaging Array
Exposure Center
Air
Water
Imaging Array
Exposure Center
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]