Fractal image compression based on fuzzy theory

Though progress has been made in fractal compression techniques, the long encoding times still remain the main drawback of this technique, which results from the need of performing a large number of range-domain matches. The total encoding time is the sum of the time required to perform each match. In order to make this method more efficient in practical use, the fuzzy theory based on feature extraction of the projection and normalized codebook method has been provided to optimize the encoding time, based on the c-means clustering approach. The results of the implementation of Rate Mean Square (RMS), Peak signal noise ratio (PSNR) and the encoding time of this proposed method have been compared to other methods like the Feature Extraction and Self-orgarnization methods to show its efficiency.