In this paper, we implemented both sequential and parallel version of fractalimage compression algorithms using CUDA (Compute Unified Device Architecture)programming model for parallelizing the program in Graphics Processing Unit formedical images, as they are highly similar within the image itself. There areseveral improvement in the implementation of the algorithm as well. Fractalimage compression is based on the self similarity of an image, meaning an imagehaving similarity in majority of the regions. We take this opportunity toimplement the compression algorithm and monitor the effect of it using bothparallel and sequential implementation. Fractal compression has the property ofhigh compression rate and the dimensionless scheme. Compression scheme forfractal image is of two kind, one is encoding and another is decoding. Encodingis very much computational expensive. On the other hand decoding is lesscomputational. The application of fractal compression to medical images wouldallow obtaining much higher compression ratios. While the fractal magnificationan inseparable feature of the fractal compression would be very useful inpresenting the reconstructed image in a highly readable form. However, like allirreversible methods, the fractal compression is connected with the problem ofinformation loss, which is especially troublesome in the medical imaging. Avery time consuming encoding pro- cess, which can last even several hours, isanother bothersome drawback of the fractal compression.
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