Automatic Compression for Image Sets Using a Graph Theoretical Framework

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.