Peer adjacent mapping with optimum parameters for fractal image compression on medical images

In order to reduce fractal image compression (FIC) computational complexity, this paper presents a novel approach based on peer adjacent and mean difference method in mapping the domain and range blocks. It allows the substitution of the costly process of the domain and range mapping with straight-forward peer adjacent schemes. The optimum parameters are suggested in terms of quadtree threshold, range sizes and number of iterations to fine-tune the output. Simulations on real computed radiography images show that the proposed method with optimum parameters yields a considerable peak signal-to-noise ratio (PSNR) value above 48 dB, reducing the runtime by as much as 19.32 s with the highest compression ratio is 20.03. Comparison with the standard FIC method confirms that our method not only accelerated the domain-range mapping procedure but also provided a high compression ratio with remarkable visual quality.