Information-theoretic metrics based on signal-to-noise ratio have long been established as providing an overall assessment of image quality, and more recently have been applied in the context of digital photography and digital printing. Such metrics are in fact ideally suited to the overall evaluation of imaging systems where the chain from scenecapture to final print may be a complicated one involving diverse technologies. This present study considers the signal-to-noise requirements for high-quality digital prints, and by consideration of the entire imaging chain accounts for signal-to-noise ratio (SNR) loss due to each significant component in this chain. By these means it is possible to distinguish the respective roles of the capture and print technologies and establish the fundamental imaging requirements for high-quality prints.