{"id":{"repo_id":"duquesne","oai_identifier":"oai:dsc.duq.edu:etd-2242"},"canonical_url":"https://search.dev.ndltd.org/etd/duquesne/oai:dsc.duq.edu:etd-2242","repository":{"repo_id":"duquesne","name":"Duquesne","base_url":"https://dsc.duq.edu/do/oai/"},"display":{"title":"Color Models for Image Decomposition","abstract":"Decomposing an image into components provides a method through which meaningful information can be extracted from an image. This work is a study of image decomposition techniques for color images. The decomposition of color images presents a new challenge since the choice of the color model has an effect on the resulting images. The color models are tested for both structure + noise and cartoon + texture decomposition. Numerical results demonstrate the behavior of the decomposition techniques for three different color models: RGB, HSI and CB.","abstract_html":"Decomposing an image into components provides a method through which meaningful information can be extracted from an image. This work is a study of image decomposition techniques for color images. The decomposition of color images presents a new challenge since the choice of the color model has an effect on the resulting images. The color models are tested for both structure + noise and cartoon + texture decomposition. Numerical results demonstrate the behavior of the decomposition techniques for three different color models: RGB, HSI and CB.","abstract_has_math":false,"creators":["Sovak, Melissa"],"institution":null,"degree_name":"MS","degree_level":"Immediate Access","degree_discipline":"Computational Mathematics","degree_department":null,"school":null,"contributors":["Stacey Levine","John Fleming","Kathleen Taylor"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2006,"date_issued":"2006-01-01T08:00:00Z","date_published":"2006-01-01T08:00:00Z","updated_at":"2026-07-24T02:10:29Z","subjects":["image decomposition","image processing","noise removal"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dsc.duq.edu/etd/1226","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Stacey Levine","John Fleming","Kathleen Taylor"]},{"key":"dc:creator","label":"Author","values":["Sovak, Melissa"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-08-03T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computational Mathematics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Immediate Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["image decomposition","image processing","noise removal"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dsc.duq.edu/etd/1226"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Decomposing an image into components provides a method through which meaningful information can be extracted from an image. This work is a study of image decomposition techniques for color images. The decomposition of color images presents a new challenge since the choice of the color model has an effect on the resulting images. The color models are tested for both structure + noise and cartoon + texture decomposition. Numerical results demonstrate the behavior of the decomposition techniques for three different color models: RGB, HSI and CB."]},{"key":"dc:title","label":"Title","values":["Color Models for Image Decomposition"]}]}],"canonical_facts":{"dc:contributor":["Stacey Levine","John Fleming","Kathleen Taylor"],"dc:creator":["Sovak, Melissa"],"dc:date.available":["2018-08-03T07:00:00Z"],"dc:description.abstract":["Decomposing an image into components provides a method through which meaningful information can be extracted from an image. This work is a study of image decomposition techniques for color images. The decomposition of color images presents a new challenge since the choice of the color model has an effect on the resulting images. The color models are tested for both structure + noise and cartoon + texture decomposition. Numerical results demonstrate the behavior of the decomposition techniques for three different color models: RGB, HSI and CB."],"dc:identifier":["https://dsc.duq.edu/etd/1226"],"dc:language":["English"],"dc:subject":["image decomposition","image processing","noise removal"],"dc:title":["Color Models for Image Decomposition"],"thesis:degree_discipline":["Computational Mathematics"],"thesis:degree_level":["Immediate Access"],"thesis:degree_name":["MS"]},"updated_at":"2026-07-24T02:10:29Z"}