Feature vector method for fast fractal image encoding is considered as one of the most innovative and promising approaches

but it suffers from several drawbacks

especially high dimensionality of feature vectors.Thus

an alternative feature method to reduce fractal encoding time is proposed.As one of its applications

cross trace-based fast fractal algorithm is presented

where the cross trace is a newly-defined feature of an image block.The proposed algorithm converts the range-domain block matching problem to the neighborhood search problem in the sense of cross trace.A simulation on popular 256×256 Lena image shows that

depending on the search window size

the proposed algorithm not only can achieve the speed-up of over 3 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 100 times or more at the cost of tolerable degradation of the decoded image quality.