Image restoration using sub-images and confidence intervals

<p>In applications, images are recorded, blurred, and noisy. This work aims to compute confidence intervals for quantifying the uncertainty of a reconstructed image. By partitioning the image into sub-images, the algorithm remains effective while becoming more efficient. Sub-images also provide flexibility to focus on a local reconstruction, focusing on the parts of the image with the most importance. Many time-sensitive applications require signal restoration and would benefit from this reconstruction process.</p>

Name thesis:degree_name

Master of Science (MS) in Mathematics

Level thesis:degree_level

Thesis: EWU Only

Discipline thesis:degree_discipline

Mathematics

Year

2022

Author dc:creator

• Babcock, Jasen

• Mathematics
• Other Applied Mathematics
• Theory and Algorithms

Statement dc:rights

• Access perpetually restricted to EWU users with an active EWU NetID

Repository record dc:identifier

https://dc.ewu.edu/theses/742

OAI identifier oai:identifier

oai:dc.ewu.edu:theses-1742