Inverse problem and approximation of fractal-like images

In this paper we consider an inverse problem and an approximation problem for fractal images. The inverse problem involves finding the Iterated Function System (IFS) parameters for a class of signals that are exactly generated via an IFS. We make use of the wavelet transform and of the image moments to solve the inverse problem. The approximation problem involves finding a fractal IFS generated image whose moments either match exactly or in a mean squared error sense a range of moments of the original image. The approximating measures are generated by an IFS model of a special form, and provide a general basis for the approximation of arbitrary images. Experimental results verifying our approach are presented