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We propose a new approach to reconstruct nondiscrete models from gridded volume samples. As a model, we use quadratic trivariate super splines on a uniform tetrahedral partition. We discuss the smoothness and approximation properties of our model and compare to alternative piecewise polynomial constructions. We observe as a non-standard phenomenon that the derivatives of our splines yield optimal approximation order for smooth data, while the theoretical error of the values is nearly optimaldoi:10.1109/tvcg.2004.16 pmid:18579968 fatcat:wqnhfbtfxreb5k663grh5p7xyq