TY - GEN
T1 - Motion-based nonuniformity correction in DoFP polarimeters
AU - Kumar, Rakesh
AU - Tyo, J. Scott
AU - Ratliff, Bradley M.
N1 - Funding Information:
This work was made possiebin parlt by Grant 410-96-0681 from the Social Sciences and Humanities ReserchaCouncil of Canada.
PY - 2007
Y1 - 2007
N2 - Division of Focal Plane polarimeters (DoFP) operate by integrating an array of micropolarizer elements with a focal plane array. These devices have been investigated for over a decade, and example systems have been built in all regions of the optical spectrum. DoFP devices have the distinct advantage that they are mechanically rugged, inherently temporally synchronized, and optically aligned. They have the concomitant disadvantage that each pixel in the FPA has a different instantaneous field of view (IFOV), meaning that the polarization component measurements that go into estimating the Stokes vector across the image come from four different points in the field. In addition to IFOV errors, microgrid camera systems operating in the LWIR have the additional problem that FPA nonuniformity (NU) noise can be quite severe. The spatial differencing nature of a DoFP system exacerbates the residual NU noise that is remaining after calibration, and is often the largest source of false polarization signatures away from regions where IFOV error dominates. We have recently presented a scene based algorithm that uses frame-to-frame motion to compensate for NU noise in unpolarized IR imagers. In this paper, we have extended that algorithm so that it can be used to compensate for NU noise on a DoFP polarimeter. Furthermore, the additional information provided by the scene motion can be used to significantly reduce the IFOV error. We have found a reduction of IFOV error by a factor of 10 if the scene motion is known exactly. Performance is reduced when the motion must be estimated from the scene, but still shows a marked improvement over static DoFP images.
AB - Division of Focal Plane polarimeters (DoFP) operate by integrating an array of micropolarizer elements with a focal plane array. These devices have been investigated for over a decade, and example systems have been built in all regions of the optical spectrum. DoFP devices have the distinct advantage that they are mechanically rugged, inherently temporally synchronized, and optically aligned. They have the concomitant disadvantage that each pixel in the FPA has a different instantaneous field of view (IFOV), meaning that the polarization component measurements that go into estimating the Stokes vector across the image come from four different points in the field. In addition to IFOV errors, microgrid camera systems operating in the LWIR have the additional problem that FPA nonuniformity (NU) noise can be quite severe. The spatial differencing nature of a DoFP system exacerbates the residual NU noise that is remaining after calibration, and is often the largest source of false polarization signatures away from regions where IFOV error dominates. We have recently presented a scene based algorithm that uses frame-to-frame motion to compensate for NU noise in unpolarized IR imagers. In this paper, we have extended that algorithm so that it can be used to compensate for NU noise on a DoFP polarimeter. Furthermore, the additional information provided by the scene motion can be used to significantly reduce the IFOV error. We have found a reduction of IFOV error by a factor of 10 if the scene motion is known exactly. Performance is reduced when the motion must be estimated from the scene, but still shows a marked improvement over static DoFP images.
KW - Division of focal plane
KW - Focal plane array
KW - Imaging polarimeter
KW - Instantaneous field of view
KW - Microgrid sensor
KW - Spatial nonuniformity
KW - Superresolution
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U2 - 10.1117/12.731460
DO - 10.1117/12.731460
M3 - Conference contribution
AN - SCOPUS:42149130465
SN - 9780819468307
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Polarization Science and Remote Sensing III
T2 - Polarization Science and Remote Sensing III
Y2 - 29 August 2007 through 30 August 2007
ER -