ABSTRACT
This chapter highlights the importance of image interpolation and cover the traditional work in image processing. It deals with interpolation in the context of exact separable interpolation of regularly sampled data. Image interpolation is a well known topic to most researchers who are interested in image processing. Image interpolation has a wide range of applications in image processing systems. From a numerical computations perspective, the ideal interpolation formula is not practical because it relies on the use of ideal filters that are not commonly in use. Splines are piecewise polynomials with pieces that are smoothly connected. Several B-spline basis functions can be used in image interpolation. Linear interpolation enjoys large popularity due to its simplicity of implementation. Blocking arises when the support of the interpolation is finite. Ringing arises because most good synthesis functions are oscillating. Synthesis functions with sharp transitions, such as those used with nearest neighbor interpolation exacerbate this effect.
