Abstract

A novel index-of-refraction material-characterization technique using passive polarimetric imagery degraded by atmospheric turbulence is presented. The method uses a variant of the LeMaster and Cain (J. Opt. Soc. Am. A 25(9), 2170-2176 (2008)) blind-deconvolution algorithm to recover the true object (i.e., the first Stokes parameter), the degree of linear polarization, and the polarimetric-image point spread functions. Nonlinear least squares is then used to find the value of the complex index of refraction that best fits the theoretical degree of linear polarization, derived using a polarimetric bidirectional reflectance distribution function, to the turbulence-corrected degree of linear polarization. To verify the proposed material-characterization technique, experimental results of two painted metal samples are provided and analyzed. C

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