The study of human neuroreceptor systems by means of positron emission tomography (PET) and suitable radioligands has proven to be of great importance in research on normal brain functions and the pathophysiology and treatment of neuropsychiatric disorders. A for long identified goal is to produce detailed parametric maps of showing neuroreceptor binding parameters for the entire human brain in vivo. The application of wavelet filters has recently been proposed as a solution to handle the inherently low signal-to-noise ratio of PET images. In the present study we applied the wavelet approach to data obtained from 10 healthy subjects who were examined with [11C]FLB 457. This high affinity dopamine D2-receptor antagonist provides a signal from a range of regions with a hundredfold difference in receptor density and should thus be suitable for evaluation of the wavelet approach. For cross-validation purposes the data were analysed with four methods: a traditional region-of-interest (ROI) based analysis, a pixel-based analysis and two variants of wavelet-aided analyses. In both variants the wavelet filter was spatially applied, but a two-dimensional filter was used in one case and a three-dimensional one in the other. The same linear-graphical binding potential (BP) estimation step was used for all methods and the results of the three parametric mapping techniques were compared to the reference ROI-based method by calculating the average BP of representative ROIs. The pixel-based and the two-dimensional-wavelet-based methods yielded highly correlated but systematically lower values when compared to the reference ROI-based method. The approach utilising three-dimensional wavelet filters yielded BP maps with regional averages closely matching the values of the ROI-based method. The results show that the combination of three-dimensional spatial wavelet filtering with established parameter estimation procedures provides detailed, accurate maps of radioligand binding parameters. Such maps can be used for in inter-individual or multi-condition comparisons of binding parameters at subregional levels.