Single pixel computational imaging
Date
2023
Authors
Stockton, Patrick Allen, author
Bartels, Randy A., advisor
Pezeshki, Ali, committee member
Muller, Jennifer, committee member
Wilson, Jesse, committee member
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Abstract
Microscopy has a long rich history of peering into life's smallest mysteries. Ever since the first microscope, the ability to see objects that would otherwise be impossible to see with the naked eye have allowed new discoveries and modern technology has benefited tremendously. There have been many improvements on microscopes over the centuries with each improvement unlocking more knowledge as we go. Some of these advancements are the modern objective lens correcting for numerous optical aberrations, phase contrast imaging allowing nearly transparent samples to have high contrast, the confocal pinhole allowing an easy method to get optical sectioning, and super resolution microscopy surpassing the diffraction limit by several orders of magnitude. One of the most amazing things about all these discoveries is that they all rely on the same fundamental concepts. This work focuses on expanding the capabilities of single pixel imaging. Single pixel imaging is a class of imaging that encodes spatial information on a temporal signal using a single element detector; having knowledge of the encoding allows the time signal to be reconstructed to generate a spatial image. A canonical example of single pixel imaging is laser scanning microscopy (LSM). More complicated encoding systems have been developed but the basic idea for reconstruction remains the same. There are several advantages conferred to single pixel imaging such as image formation is resistant to scattering, very fast temporal response, flexibility in detector selection at a given wavelength, and exotic imaging information. My research primarily utilizes two techniques, SPatIal Frequency modulated Imaging (SPIFI) and Coherent Holographic Image Reconstruction by Phase Transfer (CHIRPT), both are explained in detail. My research aims to expand the capability's of SPIFI by providing a method for homogenizing the anisotropic resolution observed in the higher orders, additionally, I present a method of solving the inverse problem that allows the measurement matrix to more accurately represent to true image formation process there by increasing the performance of the reconstruction. I present research for CHIRPT which takes advantage of the encoded coherent phase information of two interfering beams to measure the quantitative phase of an object. I also present a new technique utilizing CHIRPT's holographic phase information to extend optical diffraction tomography to incoherent emitters which has long been an illusive task.
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Subject
diffraction
quantitative phase
tomography
optimization
computational imaging
single pixel imaging