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An important challenge in the visualization of three-dimensional volume data is the efficient processing and rendering of time-resolved sequences. Only the use of compression techniques, which allow the reconstruction of the original domain from the compressed one locally, makes it possible to evaluate these sequences in their entirety. In this paper, a new approach for the extraction and visualization of so-called time features from within time-resolved volume data is presented. Based on the asymptotic decay of multiscale representations of spatially localized time evolutions of the data, singular points can be discriminated. Also, the corresponding Lipschitz exponents, which describe the signals' local regularity, can be determined, and can be taken as a measure of the variation in time. The compression ratio and the comprehension of the underlying signal is improved if we first restore the extracted regions which contain the most important information.
Rüdiger Westermann (Tue,) studied this question.