Fractal image coding is a promising lossy compression technique in terms of achievable compression ratios and decoded image quality; However

it has the primary disadvantage of high computational demands resulting in unacceptably long encoding times. Most of the encoding times are spent on searching for the best matched block to each of range blocks in a usually large domain pool. This paper thus proposed an accelerating scheme by the determinants of normalized range and domain blocks

which can find out the best matched block to an input range block in a relatively small search neighborhood. Experimental results on three popular 512×512 test images showed that

depending on the search neighborhood size

the proposed algorithm not only can achieve the speed up of about 30 times with the same PSNR(peak signal to noise ratio) as the baseline fractal algorithm with the full search

but also can obtain the speed up of 1 [KG-*7]000 times or more at the cost of tolerable degradation of the decoded image quality.