In many undersampled imaging systems, spatial integration from the individual detector elements is the dominant component of the system point spread function (PSF). Conventional focal plane arrays (FPAs) utilize square detector elements with a nearly 100% fill factor, where fill factor is defined as the fraction of the detector element area that is active in light detection. A large fill factor is generally considered to be desirable because more photons are collected for a given pitch, and this leads to a higher signal-to-noise-ratio (SNR). However, the large active area works against super-resolution (SR) image restoration by acting as an additional low pass filter in the overall PSF when modeled on the SR sampling grid. A high fill factor also tends to increase blurring from pixel cross-talk. In this paper, we study the impact of FPA detector-element shape and fill factor on SR. A detailed modulation transfer function analysis is provided along with a number of experimental results with both simulated data and real data acquired with a midwave infrared (MWIR) imaging system. We demonstrate the potential advantage of low fill factor detector elements when combined with SR image restoration. Our results suggest that low fill factor circular detector elements may be the best choice. New video results are presented using robust adaptive Wiener filter SR processing applied to data from a commercial MWIR imaging system with both high and low detector element fill factors.