Many imaging applications require the acquisition of a time series of images. In conventional Fourier transform-based imaging methods, each of these images is acquired independently. As a result, the temporal resolution possible is limited by the number of data points collected for each data set, or one often was to sacrifice spatial resolution for temporal resolution. To overcome this problem, several "data-sharing" methods have been proposed which acquire one or more high-resolution reference images and a sequence of reduced dynamic data sets. This paper is devoted to the discussion of a generalized series-based dynamic imaging method, which is an optimal implementation of the data-sharing principle. Several application examples are also presented to illustrate its effectiveness for high-resolution dynamic imaging.