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Design Of Accurate And Smooth Filters For Function And Derivative Reconstruction


The correct choice of function and derivative reconstruction filters is paramount to obtaining highly accurate renderings. Most filter choices are limited to a set of commonly used functions, and the visualization practitioner has so far no way to state his preferences in a convenient fashion. Much work has been done towards the design and specification of filters using frequency based methods. However, for visualization algorithms it is more natural to specify a filter in terms of the smoothness of the resulting reconstructed function and the spatial reconstruction error. Hence, in this paper, we present a methodology for designing filters based on spatial smoothness and accuracy criteria. We first state our design criteria and then provide an example of a filter design exercise. We also use the filters so designed for volume rendering of sampled data sets and a synthetic test function. We demonstrate that our results compare favorably with existing methods.

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Supplemental Material
Paper in Conference Proceedings or in Workshop Proceedings (Full Paper in Proceedings)
Event Title
IEEE Symposium on Volume Visualization 1998
Visualization and Data Analysis
Event Location
North Carolina
Event Type
Event Dates
19-20 Oct.
October 1998
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