Date of Award
Doctor of Philosophy (PhD)
Department of Electrical and Computer Engineering
Jason D. Schmidt, PhD
In this research, an algorithm is developed to estimate the index of refraction of an unknown object using passive polarimetric images degraded by atmospheric turbulence. The algorithm uses a variant of the maximum-likelihood blind-deconvolution algorithm developed by LeMaster and Cain 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 which 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 algorithm, experimental results of two painted metal samples are provided and analyzed. Possible uses of this novel algorithm include intelligence-gathering and nondestructive inspection/evaluation applications such as corrosion and crack detection/characterization.
DTIC Accession Number
Hyde, Milo W. IV, "Determining the Index of Refraction of an Unknown Object Using Passive Polarimetric Imagery Degraded by Atmospheric Turbulence" (2010). Theses and Dissertations. 1970.