polarimetric imaging sensors for surveillance navigation and communications howard schultz and...
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Polarimetric Imaging Sensors for Surveillance Navigation and Communications
Howard Schultz and Andrés Corrada-EmmanuelUniversity of Massachusetts, Aerial Imaging and Remote Sensing Laboratory
[email protected], [email protected]
Chris Zappa and Michael BannerColumbia University, Lamont-Doherty Earth [email protected], [email protected]
Office of Naval ResearchJanuary 3, 2007
Long Term Goals
• Develop passive remote sensing techniques for studying the dynamics of the upper ocean
• View the surface environment from a submerged platform– Polarimetric Periscope– Uplink/downlink Communications
Optical Flattening
Motivation
• View the above-surface environment from below the surface
• Objects in a scene taken from underwater are naturally blurred by wave motion– Image sharpening– wave estimation algorithm
• Wave estimates are not yet accurate enough to substantially improve the reconstructed images above the surface beyond what can be achieved assuming a flat surface.
Optical Flattening
• Use information about the 2D slope field of the ocean surface to remove image distortion -- What would an image taken through the ocean surface look like if there were no waves?
• Real-time processing
Projective Image Formation Model
Imaging Array
Exposure Center
Observation RaysAir
Water
Optical Flattening Algorithm*
• Collect polarimetric images
• Recover the 2D surface slope field
• Compute the refraction for each rays as it passes through the air-sea interface
• Create an undistorted image (sort on the direction of the rays in air)
*Patent Pending Process, University of Massachusetts, Amherst
Degree of Linear Polarization (DoLP) vs. Incidence angle
Incidence Angle (degrees)0 10 20 30 40 50 60 70 80 90
1.0
0.8
0.6
0.4
0.2
0.0
Reflection
Refraction
I
UQDoLP
22
Ray tracing image formation modelA lens maps incidence angle θ to image position X
Lens
Imaging Array
X
θ
Ray tracing image formation modelA lens maps incidence angle θ to image position X
X
θ
Lens
Imaging Array
Ray tracing image formation modelA lens maps incidence angle θ to image position X
X
Lens
Imaging Array
Ray tracing image formation modelA lens maps incidence angle θ to image position X
X
θ
Lens
Imaging Array
Ray tracing image formation modelA lens maps incidence angle θ to image position X
X
θ
Lens
Imaging Array
Refraction
Air
Water
Distorted Image Point
Refraction
Air
Water
Distorted Image Point
UndistortionCompensating for Refraction
Undistorted Image PointDistorted Image Point
Air
Water
Air
UndistortionCompensating for Refraction
Distorted Image Point Undistorted Image Point
Air
Water
Air
Implementation Considerations
• Uses only one polarimetric camera• Exploit the natural time scale separation
tsky > tobjjects > twaves > tshutter to estimate the polarization distribution of the sky radiance
• Real-time requires a functional approximation between the inferred incoming Stokes vector, the observed scattered Stokes vector and surface slope (Kattawar, 1994; Voss and Fry, 1984; Sabbah and Shashar, 2006; current effort in RaDyO).
• Statistical techniques will always be needed to sharpen final image.
• Requires a precise motion package
