In this paper we present a novel algorithm to optimize the reconstruction from non-uniform point sets. We introduce a statistically-derived topology controller for selecting the reconstruction resolution of a given non-uniform point set. Deriving information from homology-based statistics, our topology-controller ensures a stable and sound basis for the analysis process. By analysing our topology-controller, we select an optimal reconstruction resolution which ensures both low reconstruction errors and a topological stability of the underlying signal. Our approach offers a valuable method for the evaluation of the reconstruction process without the need of visual inspection of the reconstructed datasets. By means of qualitative results we show how our proposed topology statistics provides complementary information in the enhancement of existing reconstruction pipelines in visualization.