Attribute cluster network and fractal image compression

The greatest disadvantage of fractal image compression is the length of time it takes; so this paper advises using attribute cluster network (ACN) to reduce the time complexity. Using ACN can classify the feature vectors of domain blocks and range blocks, and the searching complexity can be reduced. Moreover, the weight values from ACN indicate the importance of all the points, and the new feature vectors can be got only by picking up more important points from a block, which will reduce the needed memory and improve encoding speed and clustering speed. Experiments show that combining the attribute cluster network and fractal block coding together costs less encoding time and clustering time than the other methods; that is to say, the chosen important points can replace the block itself properly.