A new automatic compression scheme that adapts to any image set is presented in this thesis.
The proposed scheme requires no a priori knowledge on the properties of the image
set. This scheme is obtained using a unified graph-theoretical framework that allows for
compression strategies to be compared both theoretically and experimentally. This strategy
achieves optimal lossless compression by computing a minimum spanning tree of a
graph constructed from the image set. For lossy compression, this scheme is near-optimal
and a performance guarantee relative to the optimal one is provided. Experimental results
demonstrate that this compression strategy compares favorably to the previously proposed
strategies, with improvements up to 7% in the case of lossless compression and 72% in
the case of lossy compression. This thesis also shows that the choice of underlying compression
algorithm is important for compressing image sets using the proposed scheme. / x, 77 leaves ; 29 cm.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:ALU.w.uleth.ca/dspace#10133/538 |
| Date | January 2007 |
| Creators | Gergel, Barry, University of Lethbridge. Faculty of Arts and Science |
| Contributors | Cheng, Howard |
| Publisher | Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2007, Faculty of Arts and Science, Department of Mathematics and Computer Science |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Relation | Thesis (University of Lethbridge. Faculty of Arts and Science) |
Page generated in 0.023 seconds