Fractal Image Compression Coding Using Logistic Mapping and Julia Collecting
Zhao De-ping · Journal of Shenyang Jianzhu University · 2006
The paper is done in order to apply the Logistic mapping to fractal image compressing so that the traditional means of fractal imagecompression can be improved.By making use of the time escaping arithmetic of Julia collecting F(Z)=Z~2+C,different curves corresponding to different C are established.Via using Logistic mapping chaos mapping function to create random integers between 0～255 to fill quantized table.After that according to the grey-scale quantized formula,the one thousandth quantized table is used to quantize the Julia image block to form the stationary dictionary.By comparing the quantized Julia image block with the block from the original image,a block whose distance is the minimum in Hausdorff measurement is chosen and its corresponding fractal parameter is saved.In decoding,the one thousandth quantized table is reconstructed to rebuild the original image.Compared with the traditional fractal coding method,this way not only can get abundant and fixed dictionary but also the course of decoding is very fast and the rebuilt image is of high quality.Through using Logistic mapping function as well as replacing the variable compressing dictionary with a fixed one,it is universal and has a high coding speed.The experiment has proved that this method is very feasible and can obtain very good result.