Reconstructing images from measurements with small pixels below the system's resolution limit theoretically results in image noise reduction compared with measurements with larger pixels. We evaluate and quantify this effect using data acquired with the small pixels of a photon-counting (PC) computed tomography scanner that can be operated in different detector pixel binning modes and with a conventional energy-integrating (EI) detector. An anthropomorphic abdominal phantom that can be extended to 3 sizes by adding fat extension rings, equipped with iodine inserts as well as human cadavers, was measured at tube voltages ranging from 80 to 140 kV. The images were acquired with the EI detector (0.6 mm pixel size at isocenter) and the PC detector operating in Macro mode (0.5 mm pixel size at iso) and ultrahigh-resolution (UHR) mode (0.25 mm pixel size at iso). Both detectors are components of the same dual-source prototype computed tomography system. During reconstruction, the modulation transfer functions were matched to the one of the EI detector. The dose-normalized contrast-to-noise ratio (CNRD) values are evaluated as a figure of merit. Images acquired in UHR mode achieve on average approximately 6% higher CNRD compared with Macro mode at the same spatial resolution for a quantitative D40f kernel. Using a sharper B70f kernel, the improvement increases to 21% on average. In addition, the better performance of PC detectors compared with EI detectors with regard to iodine imaging has been evaluated by comparing CNRD values for Macro and EI. Combining both of these effects, a CNRD improvement of up to 34%, corresponding to a potential dose reduction of up to 43%, can be achieved for D40f. Reconstruction of UHR data with a modulation transfer function below the system's resolution limit reduces image noise for all patient sizes and tube voltages compared with standard acquisitions. Thus, a relevant dose reduction may be clinically possible while maintaining image quality.