Author Affiliations

J. Scott Tyo,2Dennis L. Goldstein,3David B. Chenault,4and Joseph A. Shaw5

1When this study was performed, J. S. Tyo (tyo
ieee.org) was with the department of Electrical and Computer Engineering, college of new Mexico, Albuquerque, brand-new Mexico 87131.

You are watching: Review of passive imaging polarimetry for remote sensing applications

2He is now with the college of Optical Sciences, university of Arizona, Tucson, Arizona 85721.

3D. L. Goldstein (dennis.goldstein
eglin.af.mil) is with the U.S. Air pressure Research Laboratory∕MNGI, Eglin Air pressure Base, Florida 32542.

4D. B. Chenault (david
polarissensor.com) is v Polaris Sensor Technologies, Incorporated, 200 West side Square, Suite 320, Huntsville, Alabama 35801.

5J. A. Demonstrate (jshaw
ece.montana.edu) is with the department of Electrical and also Computer Engineering, Montana State University, Bozeman, Montana 59717.

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*

J. Scott Tyo, Dennis L. Goldstein, David B. Chenault, and Joseph A. Shaw, "Review of passive imaging polarimetry because that remote sensing applications," Appl. Opt. 45, 5453-5469 (2006)
Previously assigned OCIS codesImaging systems (110.0110)Remote sensing and sensors (120.0280)Polarimetry (120.5410)
HistoryOriginal Manuscript: November 17, 2005Revised Manuscript: April 4, 2006Manuscript Accepted: April 6, 2006

Abstract

Imaging polarimetry has arised over the previous three years as a powerful tool to boost theinformation accessible in a variety of remote sensing applications. Wediscuss the structures of passive imaging polarimetry, the phenomenological factors fordesigning a polarimetric sensor, and the major architectures that have actually been exploited fordeveloping imaging polarimeters. Considerations top top imaging polarimeters such as calibration,optimization, and also error performance are also discussed. We review countless important sources andexamples from the scientific literature.

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References

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AdvantagesDisadvantages
Visible, NIR, SWIR• sun is a solid source• strongly dependent top top geometry
Typical signal: 1%–60%• High dynamic variety of polarization signatures• High dynamic variety of signatures
Sensor resolution: >1%–2%• Sensors cheaper, less complicated to build and calibrate• Inconsistent signatures
• small well dimension for FPAs limits
polarimetric resolution
• No night operation
MWIR• an excellent signatures for hot targets• Signatures combination of
Typical signal: 0.1%–25%• Night operationemissive and reflective
Sensor resolution: >0.2%• huge well sizes because that FPA for much better sensitivity• Sensors call for cooling
• Sensors much more expensive and
difficult come build and calibrate
LWIR• Signatures dominated by emission• Sensors require cooling
Typical signal: 0.1%–20%• much less dynamic range for polarization signatures• Sensors most expensive and
Sensor resolution: • Night operation

Close
×Table 2
Comparison that Imaging Polarimetry Architectures
Design FeaturesFabrication–Integration Issues, CostMisregistration IssuesDivision of aperture (single FPA)
Rotating element• Robust• most basic to implement• Scene and also platform motion
• reasonably small• Inexpensive• Beam wander not a problem
• Not suitable for dynamicor gotten rid of in software
scenes• Misregistration is linear
Division the amplitude• simultaneously acquisition• High mechanical flexibility• should register lot of FPAs
(multiple FPAs)• large system sizeand rigidity required• Misregistration deserve to be fixed
• Expensive• have the right to be nonlinear
• Large
• simultaneously acquisition• lose of spatial resolution• solved misregistration
• smaller sized size• Expensive• can be nonlinear
Division of focal distance plane• simultaneous acquisition• Fabrication difficult• IFOVs misregistered
• little and rugged• Alignment difficult• needs interpolation
• loss of spatial resolution• an extremely expensive• solved registration
Coboresighted• coincided acquisition• basic integration• Misregistration no as stable
• best used at lengthy ranges• Expensive

Close
×Tables (2)
Table 1

Polarization Phenomenology and Effects indigenous the clearly shows to the LWIR


AdvantagesDisadvantagesVisible, NIR, SWIR
• sunlight is a solid source• strong dependent ~ above geometry
Typical signal: 1%–60%• High dynamic variety of polarization signatures• High dynamic variety of signatures
Sensor resolution: >1%–2%• Sensors cheaper, simpler to build and also calibrate• Inconsistent signatures
• tiny well size for FPAs limits
polarimetric resolution
• No night operation
MWIR• great signatures for warm targets• Signatures mix of
Typical signal: 0.1%–25%• Night operationemissive and also reflective
Sensor resolution: >0.2%• huge well sizes for FPA for better sensitivity• Sensors require cooling
• Sensors more expensive and
difficult come build and also calibrate
LWIR• Signatures conquered by emission• Sensors call for cooling
Typical signal: 0.1%–20%• less dynamic range for polarization signatures• Sensors many expensive and
Sensor resolution: • Night operation

Design FeaturesFabrication–Integration Issues, CostMisregistration IssuesDivision of aperture (single FPA)
Rotating element• Robust• simplest to implement• Scene and platform motion
• reasonably small• Inexpensive• Beam wander not a problem
• Not perfect for dynamicor eliminated in software
scenes• Misregistration is linear
Division the amplitude• simultaneously acquisition• High mechanically flexibility• have to register multiple FPAs
(multiple FPAs)• large system sizeand rigidity required• Misregistration deserve to be fixed
• Expensive• can be nonlinear
• Large
• simultaneously acquisition• ns of spatial resolution• solved misregistration
• smaller sized size• Expensive• can be nonlinear
Division of focal length plane• simultaneously acquisition• Fabrication difficult• IFOVs misregistered
• small and rugged• Alignment difficult• needs interpolation
• ns of spatial resolution• an extremely expensive• fixed registration
Coboresighted• simultaneously acquisition• basic integration• Misregistration no as stable
• best used at long ranges• Expensive