We present some issues that arise when a geometric transformation is performed on an image or a volume. In particular, we illustrate the well-known problems of blocking, blurring, aliasing and ringing. Although the solution to these problems is trivial in an analog (optical) image processing system, their solution in a discrete (numeric) context is much more difficult. The modern trend of biomedical image processing is to fight these artifacts by using more sophisticated models that emphasize the quality of interpolation. For example, spline kernels offer excellent performances for a low computational cost; in addition, this compromise can be tuned by controlling the degree of the spline.