Date of Award

9-2023

Document Type

Thesis

Degree Name

Master of Science in Electrical Engineering

Department

Department of Electrical and Computer Engineering

First Advisor

Stephen C. Cain, PhD

Abstract

Imaging through turbulence is affected by several factors including imaging system specifications, imaging system setup and more importantly the atmospheric turbulence as it is uncontrollable. One important parameter which is used to quantify the atmospheric turbulence severity is the atmospheric coherence diameter (π‘Ÿ0 ), known as Fried's parameter. This thesis explores ways to characterize the atmospheric turbulence effects on image quality using simulated and laboratory generated turbulence where π‘Ÿ0 is estimated using a maximum a posteriori (MAP) estimator and frequency domain analysis algorithms. Furthermore, image quality metrics such as Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM) and Quality Index based on Local Variance (QILV) are compared against each other in terms of detecting simulated atmospheric turbulence and read-out noise. Finally, these image quality metrics are used to assess the quality of deconvolved images using a Wiener filter and a maximum likelihood algorithm.

AFIT Designator

AFIT-ENG-MS-23-S-062

DTIC Accession Number

AD1341282

Comments

An embargo was observed for posting this thesis on AFIT Scholar.

Approved for public release, PA case number 88ABW-2023-0818

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