1. 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 Howard Schultz Chris J. Zappa, Michael L. Banner, Larry Pezzaniti Howard Schultz Howard Schultz Chris J. Zappa, Michael L. Banner, Larry Pezzaniti August 2010

2. 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

3. 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

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. 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 reflection or scattering is governed by Muller Calculus S OUT = M S IN Where M contains information about the shape and material properties of the scattering media The goal: Measure S OUT and S IN and infer the parameters of M What is polarimetry? Amount of circular polarization Orientation and degree of linear polarization Intensity Incident Light Muller Matrix Scattered Light

8. 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 polarimeters field-of-view

9. What is the Polarimetric Slope Sensing (PSS) technique?

10. 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

12. Looking at 90 to the waves Looking at 45 to the waves Looking at 0 to the waves

14. Slope in Degrees X-Component Y-Component

15. X-ComponentY-Component

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

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

21. 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

22. X and Y Slope Video

23. Reconstructed Surface Video

24. Preliminary Polarimeter Comparison with Cox and Munk

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

26. Optical Flattening

27. 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 Formation Subsurface-to-surface Imaging Array Exposure Center Observation Rays Air Water

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

30. 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

31. Un-distortion A lens maps incidence angle θ to image position X Lens Imaging Array X θ

32. X θ Lens Imaging Array Un-distortion A lens maps incidence angle θ to image position X

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

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

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

36. Distorted Image Point Image array Un-distortion Use the refraction angle to straighten out light rays Air Water

37. Air Water Distorted Image PointUn-distorted Image Point Image array Un-distortion Use the refraction angle to straighten out light rays

38. 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

39. 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

40. 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