Imaging polarimetry has emerged over the past three decades as a powerful tool to enhance the information available in a variety of remote sensing applications. We discuss the foundations of passive imaging polarimetry, the phenomenological reasons for designing a polarimetric sensor, and the primary architectures that have been exploited for developing imaging polarimeters. Considerations on imaging polarimeters such as calibration, optimization, and error performance are also discussed. We review many important sources and examples from the scientific literature.

The relationship between system condition and signal-to-noise ratio (SNR) in reconstructed Stokes parameter images is investigated for rotating compensator, variable retardance, and rotating analyzer Stokes vector (SV) polarimeters. A variety of optimal configurations are presented for each class of systems. The operation of polarimeters is discussed in terms of a four-dimensional conical vector space; and the concept of nonorthogonal bases, frames, and tight frames is introduced to describe the operation of SV polarimeters. Although SNR is an important consideration, performance of a polarimeter in the presence of errors in the calibration and alignment of the optical components is also important. The relationship between system condition and error performance is investigated, and it is shown that an optimum system from the point of view of SNR is not always an optimum system with respect to error performance. A detailed theory of error performance is presented, and the error of a SV polarimeter is shown to be related to the stability and condition number of the polarization processing matrices. The rms error is found to fall off as the inverse of the number of measurements taken. Finally, the concepts used to optimize SV polarimeters are extended to be useful for full Mueller matrix polarimeters.

Polarization-difference imaging (PDI) was recently presented by us as a method of imaging through scattering media [Opt. Lett. 20, 608 (1995)]. Here, PDI is compared with conventional, polarizationblind imaging systems under a variety of conditions not previously studied. Through visual and numerical comparison of polarization-difference and polarization-sum images of metallic targets suspended in scattering media, target features initially visible in both types of images are shown to disappear in polarization-sum images as the scatterer concentration is increased, whereas these features remain visible in polarization-difference images. Target features producing an observed degree of linear polarization of less than 1% are visible in polarization-difference images. The ability of PDI to suppress partially polarized background variations selectively is demonstrated, and discrimination of target features on the basis of polarization information is discussed. Our results show that, when compared with conventional imaging, PDI yields a factor of 2-3 increase in the distance at which certain target features can be detected.

No abstract