Abstract-Fractals are geometric patterns generated by Iterated Function System theory. A popular technique known as fractal image compression is based on this theory, which assumes that redundancy in an image can be exploited by block-wise selfsimilarity and that the original image can be approximated by a finite iteration of fractal codes. This technique offers high compression ratio among other image compression techniques. However, it presents several drawbacks, such as the inverse proportionality between image quality and computational cost. Numerous approaches have been proposed to find a compromise between quality and cost. As an efficient optimization approach, genetic algorithm is used for this purpose. In this paper, a crowding method, an improved genetic algorithm, is used to optimize the search space in the target image by good approximation to the global optimum in a single run. The experimental results for the proposed method show good efficiency by decreasing the encoding time while retaining a high quality image compared with the classical method of fractal image compression.
As known, in general topology the talking be about “nearness”. This is exactly needed to discuss subjects such convergence and continuity. The simple way to study about nearness is to correspond the set with a distance function to inform us how far apart two elements of are. The metric concept introduced by a French mathematician Maurice René Fréchet (1878 – 1973) in 1906 in his work on some points of the functional calculus. However, the name is due to a German mathematician Felix Hausdorff (1868 –1942) who is considered to be one of the founders of modern topology. In addition to these contribution, he contributed significantly to set theory, descriptive set theory, measure theory, and functional analysis.
Fractals have gained great attention from researchers due to their wide applications in engineering and applied sciences. Especially, in several topics of applied sciences, the iterated function systems theory has important roles. As is well known, examples of fractals are derived from the fixed point theory for suitable operators in spaces with complete or compact structures. In this article, a new generalization of Hausdorff distance on , is a class of all nonempty compact subsets of the metric space ( , ). Completeness and compactness of are analogously obtained from its counterparts of ( , ). Furthermore, a fractal is presented under a finite set of generalized -contraction mappings. Also, other special cases are presented.
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