자료유형  

 학위논문

Control Number  

0016932689

International Standard Book Number  

9798379834371

Dewey Decimal Classification Number  

500

Main Entry-Personal Name  

Reid, Emma.

Publication, Distribution, etc. (Imprint  

[S.l.] : Purdue University., 2021

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2021

Physical Description  

1 online resource(85 p.)

General Note  

Source: Dissertations Abstracts International, Volume: 85-01, Section: B.

General Note  

Advisor: Buzzard, Gregery;Bouman, Charles.

Dissertation Note  

Thesis (Ph.D.)--Purdue University, 2021.

Restrictions on Access Note  

This item must not be sold to any third party vendors.

Summary, Etc.  

요약Applications in materials and biological imaging are currently limited by the ability to collect high-resolution data over large areas in practical amounts of time. One possible solution to this problem is to collect low-resolution data and apply a super-resolution interpolation algorithm to produce a high-resolution image. However, state-of-the-art superresolution algorithms are typically designed for natural images, require aligned pairing of high and low-resolution training data for optimal performance, and do not directly incorporate a data-fidelity mechanism.We present a Multi-Resolution Data Fusion (MDF) algorithm for accurate interpolation of low-resolution SEM and TEM data by factors of 4x and 8x. This MDF interpolation algorithm achieves these high rates of interpolation by first learning an accurate prior model denoiser for the TEM sample from small quantities of unpaired high-resolution data and then balancing this learned denoiser with a novel mismatched proximal map that maintains fidelity to measured data. The method is based on Multi-Agent Consensus Equilibrium (MACE), a generalization of the Plug-and-Play method, and allows for interpolation at arbitrary resolutions without retraining. We present electron microscopy results at 4x and 8x super resolution that exhibit reduced artifacts relative to existing methods while maintaining fidelity to acquired data and accurately resolving sub-pixel-scale features.

Subject Added Entry-Topical Term  

Transmission electron microscopy.

Subject Added Entry-Topical Term  

E coli.

Subject Added Entry-Topical Term  

Crystals.

Subject Added Entry-Topical Term  

Inverse problems.

Subject Added Entry-Topical Term  

Sensors.

Subject Added Entry-Topical Term  

Neural networks.

Subject Added Entry-Topical Term  

Scanning electron microscopy.

Subject Added Entry-Topical Term  

Analytical chemistry.

Subject Added Entry-Topical Term  

Chemistry.

Subject Added Entry-Topical Term  

Mathematics.

Added Entry-Corporate Name  

Purdue University.

Host Item Entry  

Dissertations Abstracts International. 85-01B.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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Control Number  

joongbu:643312