In this paper we are concerned with the end-to-end performance of image gathering, coding, and restoration as a whole rather than as a chain of independent tasks. Our approach evolves from the pivotal relationship that exists between the spectral information density of the transmitted signal and the restorability of images from this signal. The results of this assessment lead to intuitively appealing insights about image gathering and coding for digital restoration. Foremost is the realization that images can be restored with better quality and from less data as the information efficiency of the transmitted data is increased. Another important realization is that the critical constraints imposed on both image gathering and natural vision limit the maximum acquired information density to approximately 4 binary information units (bifs). If the data are digitally restored as an image on film, the information density may be reduced to less than 3 bifs. The higher information density of approximately 4 bifs that the eye can acquire probably contributes effectively to the improvement in visual quality that we always experience when we view a scene directly rather than through the media of image gathering and restoration.