Entropy measures for controlled coding

In this paper, we present an approach to characterize video sequences using information theoretic measures. This characterization is then used to efficiently represent a volume of video. In a typical video sequence, sometimes texture reveals structure, in other cases motion does it. In addition, the temporal and spatial extents are variables. The attempt of this work is to build this structure by looking at a given region over a multiplicity of frames and scales using entropy measures. We then present a hierarchically structured class of coders that efficiently represent this volume of video. The structure built in the analysis stage is used to control and select amongst this class of coders.

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