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.
","abstract_html":"<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>","abstract_has_math":false,"creators":["Babcock, Jasen"],"institution":null,"degree_name":"Master of Science (MS) in Mathematics","degree_level":"Thesis: EWU Only","degree_discipline":"Mathematics","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-01-01T08:00:00Z","date_published":"2022-01-01T08:00:00Z","updated_at":"2026-07-24T02:12:39Z","subjects":["Mathematics","Other Applied Mathematics","Theory and Algorithms"],"languages":[],"rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.ewu.edu/theses/742","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Babcock, Jasen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Mathematics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis: EWU Only"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS) in Mathematics"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Mathematics","Other Applied Mathematics","Theory and Algorithms"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Access perpetually restricted to EWU users with an active EWU NetID"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.ewu.edu/theses/742"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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.
"]},{"key":"dc:title","label":"Title","values":["Image restoration using sub-images and confidence intervals"]}]}],"canonical_facts":{"dc:creator":["Babcock, Jasen"],"dc:description.abstract":["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.
"],"dc:identifier":["https://dc.ewu.edu/theses/742"],"dc:rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"dc:subject":["Mathematics","Other Applied Mathematics","Theory and Algorithms"],"dc:title":["Image restoration using sub-images and confidence intervals"],"thesis:degree_discipline":["Mathematics"],"thesis:degree_level":["Thesis: EWU Only"],"thesis:degree_name":["Master of Science (MS) in Mathematics"]},"updated_at":"2026-07-24T02:12:39Z"}