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dc.contributor.supervisor Cheng, Howard Gergel, Barry University of Lethbridge. Faculty of Arts and Science 2007-11-29T16:32:34Z 2007-11-29T16:32:34Z 2007
dc.description x, 77 leaves ; 29 cm. en
dc.description.abstract 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. en
dc.language.iso en_US en
dc.publisher Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2007 en
dc.relation.ispartofseries Thesis (University of Lethbridge. Faculty of Arts and Science) en
dc.subject Dissertations, Academic en
dc.subject Data compression (Computer science) en
dc.subject Graph theory -- Data processing en
dc.title Automatic compression for image sets using a graph theoretical framework en
dc.type Thesis en
dc.publisher.faculty Faculty of Arts and Science en
dc.publisher.department Department of Mathematics and Computer Science en Masters

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