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An improvement scheme, so named the Two-Pass Improved Encoding Scheme (TIES), for the application to image compression through the extension of the existing concept of fractal image compression (FIC), which capitalizes on the self-similarity within a given image which is to be compressed, is proposed in this paper. This paper first briefly explores the existing image compression technology based on FIC, before exploring the areas which can be improved and hence establishing the concept behind the TIES algorithm. An effective encoding and decoding algorithm for the implementation of TIES is developed, through the consideration of the domain pool, block scaling and transformation, range block approximation using linear combinations and arithmetic encoding for storing data as close to source entropy as possible. The performance of TIES is then explicitly compared against that of FIC under the same conditions. Finally, due to the long encoding time required by TIES, this paper then proceeds to propose parallelized versions of the two TIES algorithms, before finally concluding with an empirical analysis of the speedup and scalability of the parallelized TIES algorithms, as well as compare the effect of parallelization between the two.

Two Pass Improved Encoding and its Parallel Processing for Fractal Image Compression