Curve Fitting by Fractal Interpolation

Fractal interpolation provides an efficient way to describe data that have an irregular or self-similar structure. Fractal interpolation literature focuses mainly on functions, i.e. on data points linearly ordered with respect to their abscissa. In practice, however, it is often useful to model curves as well as functions using fractal intepolation techniques. After reviewing existing methods for curve fitting using fractal interpolation, we introduce a new method that provides a more economical representation of curves than the existing ones. Comparative results show that the proposed method provides smaller errors or better compression ratios.