of the main disadvantages of fractal image data compression is a loss time in
the process of image compression (encoding) and conversion into a system of
iterated functions (IFS). In this paper, the idea of the inverse problem of
fixed point is introduced. This inverse problem is based on collage theorem
which is the cornerstone of the mathematical idea of fractal image compression.
Then this idea is applied by iterated function system, iterative system
functions and grayscale iterated function system down to general
transformation. Mathematical formulation form is also provided on the digital
image space, which deals with the computer. Next, this process has been revised
to reduce the time required for image compression by excluding some parts of
the image that have a specific milestone. The neural network algorithms have
been applied on the process of compression (encryption). The experimental
results are presented and the performance of the proposed algorithm is
discussed. Finally, the comparison between filtered ranges method and self-organizing
method is introduced.
Cite this paper
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