The objective of this study was to evaluate a resolution recovery (RR) method using a variety of simulated human brain [¹¹C]raclopride positron emission tomography (PET) images. Simulated datasets of 15 numerical human phantoms were processed by a wavelet-based RR method using an anatomical prior. The anatomical prior was in the form of a hybrid segmented atlas, which combined an atlas for anatomical labelling and a PET image for functional labelling of each anatomical structure. We applied RR to both 60 min static and dynamic PET images. Recovery was quantified in 84 regions, comparing the typical 'true' value for the simulation, as obtained in normal subjects, simulated and RR PET images. The radioactivity concentration in the white matter, striatum and other cortical regions was successfully recovered for the 60 min static image of all 15 human phantoms; the dependence of the solution on accurate anatomical information was demonstrated by the difficulty of the technique to retrieve the subthalamic nuclei due to mismatch between the two atlases used for data simulation and recovery. Structural and functional synergy for resolution recovery (SFS-RR) improved quantification in the caudate and putamen, the main regions of interest, from -30.1% and -26.2% to -17.6% and -15.1%, respectively, for the 60 min static image and from -51.4% and -38.3% to -27.6% and -20.3% for the binding potential (BP(ND)) image, respectively. The proposed methodology proved effective in the RR of small structures from brain [¹¹C]raclopride PET images. The improvement is consistent across the anatomical variability of a simulated population as long as accurate anatomical segmentations are provided.