Title

Image Deblurring for Material Science Applications in Optical Microscopy

Date of Award

1-1-2018

Degree Name

M.S. in Electrical Engineering

Department

Department of Electrical and Computer Engineering

Advisor/Chair

Advisor: Keigo Hirakawa

Abstract

The objective of this research is to develop an application-specific image deblurring algorithm for microscopic, material images. In microscopy, there are two types of image blur---one due to the limitation of the microscope, and another due to defocus. Defocus blur is particularly problematic in the case of spatially-varying materials, where the texture of the material surface is not flat. Through various deconvolution techniques, the image can be deblurred and high frequency components can be restored. Through our partnership with the Materials and Manufacturing Directorate at Air Force Research Lab (AFRL), we have developed an optimal deblurring method specifically for material images. We tailor our deblurring method for material images based on a priori knowledge about the characteristics of the material. The specificity of the material features allows us to impose stronger constraints on the defocus blur, which we leverage to handle spatially varying material surfaces, whose defocus blur is non-uniform across the image. The significance of this research is the development of a deblurring algorithm capable of handling a larger amount of blur and noise than the state-of-the-art methods. Currently, existing image deblurring algorithms are designed to handle diverse scene contents and blur kernels with large degrees of freedom. As a result, the existing methods can handle only small amounts of blur and noise. With the goal to handle types of images acquired by a specific microscope modality, we are able to recover finer details within the image while handling a larger degree of blur because the solution space is significantly constrained.

Keywords

Electrical Engineering, Engineering, Computer Engineering, Computer Science, Image Deblurring, Deconvolution, Optical Microscopy, Image Processing, Regularization

Rights Statement

Copyright 2018, author

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