There have been numerous applications of super-resolution reconstruction algorithms to improve the range performance of infrared imagers. These studies show there can be a dramatic improvement in range performance when super-resolution algorithms are applied to under-sampled imager outputs. These occur when the imager is moving relative to the target which creates different spatial samplings of the field of view for each frame. The degree of performance benefit is dependent on the relative sizes of the detector/spacing and the optical blur spot in focal plane space. The blur spot size on the focal plane is dependent on the system F-number. Hence, in this paper we provide a range of these sensor characteristics, for which there is a benefit from super-resolution reconstruction algorithms. Additionally, we quantify the potential performance improvements associated with these algorithms. We also provide three infrared sensor examples to show the range of improvements associated with provided guidelines.