A method of reducing the amount of data required to reconstruct an ima
ge is described. In this scheme, fully sampled low spatial frequency d
ata are acquired up to a given cutoff frequency and above this point,
only alternate lines are sampled. Two images are produced, one of low
definition and one of high definition but aliased. The proposed algori
thm unwraps the aliased data, which are then used to enhance the low p
ass image, yielding a best estimate of the true image. The reduced sam
pling technique is shown to afford biological images that are almost i
ndistinguishable from those obtained from a complete data set.