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fractal compression methods are based on iterative function systems (IFS), which was developed by Barnsley (1) and Jacquin (2). During compression, the algorithm partitions the image into a set of square blocks (domain blocks). After this a new partition is made into smaller range blocks (2). The domain blocks are generally double the size of range blocks. For every range block the nearest domain block is identified among all domain blocks after applying a set of transformations on the domain blocks. Smaller sized images are obtained by storing the information about these transformations alone. The transforms store the domain number, scaling constant, offset etc. This method of compression is called the partitioned iteration function system (PIFS). This paper explores the use of variable scaling factors for the transformation from domain to the range blocks. This variable factor has been generated using a pseudo-random number generator. The results show comparable ratios of compression and RMS error with PIFS (Partitioned iterated function systems) based fractal compression.

Randomized Algorithm for Scaling Factors in Fractal Image Compression