Date of Award

6-2018

Degree Name

MS in Electrical Engineering

Department/Program

Electrical Engineering

College

College of Agriculture, Food, and Environmental Sciences

Advisor

Jane Zhang

Advisor Department

<--Please Select Department-->

Advisor College

College of Agriculture, Food, and Environmental Sciences

Abstract

Lawrence Livermore National Laboratory's (LLNL) National Ignition Facility (NIF) uses a variety of diagnostics and image capturing optics for collecting data in High Energy Density Physics (HEDP) experiments. However, every image capturing system causes blurring and degradation of the images captured. This degradation can be mathematically described through a camera system's Point Spread Function (PSF), and can be reversed if the system's PSF is known. This is deconvolution, also called image restoration. Many PSFs can be determined experimentally by imaging a point source, which is a light emitting object that appears infinitesimally small to the camera. However, NIF's Kirkpatrick-Baez Optic (KBO) is more difficult to characterize because it has a spatially-varying PSF. Spatially varying PSFs make deconvolution much more difficult because instead of being 2-dimensional, a spatially varying PSF is 4-dimensional. This work discusses a method used for modeling the KBO's PSF by modeling it as the sum of products of two basis functions. This model assumes separability of the four dimensions of the PSF into two, 2-dimensional basis functions. While previous work would assume parametric forms for some of the basis functions, this work attempts to only use numeric representations of the basis functions. Previous work also ignores the possibility of non-linear magnification along each image axis, whereas this work successfully characterizes the KBO's non-linear magnification. Implementation of this model gives exceptional results, with the correlation coefficient between a model generated image and an experimental image as high as 0.9994. Modeling the PSF with high accuracy lays the groundwork to allow for deconvolution of images generated by the KBO.

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