Fast Fractal Image Compression Based on Fuzzy C-means Clustering

Fractal image coding can provide a high reconstructed image quality with a high compression ratio, but it suffers from long encoding time, for fractal image coding must spend long time on finding out the best-matched block from a large domain pool to represent each of range blocks. In this paper, a fast fractal image compression based on fuzzy C-means clustering is proposed, which can search out the best-matched block to an input range block with a reduced search. Firstly, the origin image is split into range blocks and domain blocks, and 8 elementary transform are performed on domain blocks to obtain the domain blocks group. Secondly, all range blocks and domain blocks group are clustered by fuzzy C-means clustering (FCM). Finally, domain block transform with the biggest fuzzy membership are encoded. Experimental results show that the proposed image coding is a fast and efficient image compression scheme; it can considerably shorten the encoding time, while achieving the same or better decoded image quality.