A fast classification based method for fractal image encoding

In the present paper a fast and efficient fractal image encoding method based on classification of image blocks is presented. Two parameters are used to sort image blocks into disjoint classes: the direction of the approximate first derivative and a normalized root mean square error of the fitting plane in the given block. With the help of these parameters the number of domain blocks examined for a range block is reduced dramatically, and thus, the classification results in a considerable acceleration of the encoding process, without loss of the reconstruction fidelity. The proposed method is compared to recently developed fast classification algorithms and a ‘No search algorithm’, and its rate-distortion performance under the same encoding time limit is proved to be better than that of the others.