In traditional fractal image compression, the encoding procedure is time-consuming due to the full search mechanism. In order to speed up the encoder, we adopt particle swarm optimization method performed under APCC based classification and sorting domain blocks with APCC using preset block to further decrease the amount of encoding time. The Fisher’s 3 classifier partitions all of the blocks in domain pool and range pool into three classes. Each range block searches the most similar block only from the blocks of the same class and Pearson correlation coefficient is calculated where comparison of range and domain block is done in same class. Furthermore, sorting of the domain blocks are with respect to APCCs between these domain blocks and a preset block in each class, the matching domain block for a range block can be searched in the selected domain set in which these APCCs are closer to APCC between the range block and the preset block. Experimental results show that, the encoding time of the proposed method is faster than that of the full search method while improving the reconstructed image quality.
Volume 11 | 08-Special Issue
Pages: 3094-3101