First Advisor

Mau Nam Nguyen

Date of Award

2-28-2020

Document Type

Thesis

Degree Name

Bachelor of Science (B.S.) in Mathematics and University Honors

Department

Mathematics and Statistics

Language

English

Subjects

Image processing, Machine learning, Image reconstruction, Nonconvex programming, Mathematical optimization

DOI

10.15760/honors.856

Abstract

This thesis explores image dictionary learning via non-convex (difference of convex, DC) programming and its applications to image reconstruction. First, the image reconstruction problem is detailed and solutions are presented. Each such solution requires an image dictionary to be specified directly or to be learned via non-convex programming. The solutions explored are the DCA (DC algorithm) and the boosted DCA. These various forms of dictionary learning are then compared on the basis of both image reconstruction accuracy and number of iterations required to converge.

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Persistent Identifier

https://archives.pdx.edu/ds/psu/32744

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