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Shape-from-Polarimetry: Recovering Sea Surface Topography

Shape-from-Polarimetry: Recovering Sea Surface Topography. Howard Schultz Department of Computer Science University of Massachusetts 140 governors Dr Amherst, MA 01003 hschultz @cs.umass.edu >. October 2011. Outline. Why recover the spatial -temporal structure of ocean waves?

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Shape-from-Polarimetry: Recovering Sea Surface Topography

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  1. Shape-from-Polarimetry: Recovering Sea Surface Topography Howard Schultz Department of Computer Science University of Massachusetts 140 governors Dr Amherst, MA 01003 hschultz@cs.umass.edu> October 2011

  2. Outline • Why recover the spatial-temporal structure of ocean waves? • Requirements • What is polarimetry? • What is the Shape-from-Polarimetry? • Build and Test an Imaging Polarimeter for Ocean Apps. • Recent Experiment and Results • Optical Flattening • Seeing Through Waves

  3. Why recover the structure of the ocean surface? • Characterize small small-scale wave dynamics and microscale breaking • Air-sea interactions occur at short wavelengths • Non-linear interaction studies require phase-resolved surface topography • Enable through-the-wave imaging • Detect anomalies in surface slope statistics • 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 • Requirements • Spatial resolution (resolve capillary waves) ~ 1mm • Temporal resolution ~60Hz sampling rate • Shutter speed < 1 msec

  4. What is polarimetry? • Light has 3 basic qualities • Color, intensity and polarization • Humans do not see polarization

  5. Linear Polarization http://www.enzim.hu/~szia/cddemo/edemo0.htm

  6. Circular Polarization

  7. Amount of circular polarization Orientation and degree of linear polarization Intensity 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) • 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 Incident Light Muller Matrix Scattered Light

  8. What is Shape-from-Polarimetry (SFP)? • 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

  9. What is Shape-from-Polarimetry (SFP)?

  10. What is Shape-from-Polarimetry (SFP)? SAW = RAWSSKYand SWA = TAWSUP

  11. What is Shape-from-Polarimetry (SFP)? • For RaDyO 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

  12. What is Shape-from-Polarimetry (SFP)?

  13. How well does the SFP 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

  14. Looking at 90 to the waves Looking at 45 to the waves Looking at 0 to the waves

  15. X-Component Y-Component Slope in Degrees

  16. X-Component Y-Component Slope in Degrees

  17. 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/

  18. Camera 3 Camera 4 Camera 1 (fixed) Polarizing beamsplitter assembly Objective Assembly Camera 2 Motorized Stage 12mm travel 5mm/sec max speed

  19. FLIP INSTRUMENTATION SETUP Scanning Altimeters Visible Camera Air-Sea Flux Package Infrared Camera Polarimeter

  20. 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

  21. Sample Results

  22. X and Y slope field

  23. Convert slope arrays to a height array Use the Fourier derivative theorem

  24. Reconstructed Surface Video

  25. Seeing Through Waves • Sub-surface to surface imaging • Surface to sub-surface imaging

  26. Optical Flattening

  27. 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

  28. Image FormationSubsurface-to-surface Observation Rays Air Water Imaging Array Exposure Center

  29. Image Formationsurface-to-subsurface Exposure Center Imaging Array Air Imaging Array Water Exposure Center

  30. Seeing Through Waves

  31. Seeing Through Waves 0 20 40 60 80 0 10 20 30 40

  32. 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

  33. Un-distortionA lens maps incidence angle θ to image position X θ Lens Imaging Array X

  34. Un-distortionA lens maps incidence angle θ to image position X θ Lens Imaging Array X

  35. Un-distortionA lens maps incidence angle θ to image position X Lens Imaging Array X

  36. Un-distortionA lens maps incidence angle θ to image position X θ Lens Imaging Array X

  37. Un-distortionA lens maps incidence angle θ to image position X θ Lens Imaging Array X

  38. Un-distortionUse the refraction angle to “straighten out” light rays Image array Air Water Distorted Image Point

  39. Un-distortionUse the refraction angle to “straighten out” light rays Image array Air Water Un-distorted Image Point

  40. 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 ✔

  41. Image Formationsurface-to-subsurface Exposure Center Imaging Array Air Imaging Array Water Exposure Center

  42. 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

  43. Questions?

  44. For more information contact Howard Schultz University of Massachusetts Department of Computer Science 140 Governors Drive Amherst, MA 01003 Phone: 413-545-3482 Email: hschultz@cs.umass.edu

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