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Duquesne

Color Models for Image Decomposition

Abstract

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.

Degree

thesis:*
Name thesis:degree_name
MS
Level thesis:degree_level
Immediate Access
Discipline thesis:degree_discipline
Computational Mathematics
Year dc:date.available
2006

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Sovak, Melissa
Contributors dc:contributor
  • Stacey Levine
  • John Fleming
  • Kathleen Taylor

Subjects

dc:subject × 3

Rights

Language dc:language
English

Identifiers

dc:identifier.*
Repository record dc:identifier
https://dsc.duq.edu/etd/1226
OAI identifier oai:identifier
oai:dsc.duq.edu:etd-2242

Chain of custody

source
Harvested from
Duquesne
Base URL
dsc.duq.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Sovak, Melissa. Color Models for Image Decomposition. Immediate Access thesis, 2006. https://dsc.duq.edu/etd/1226