Domain search using shrunken images for fractal image compression
Author(s) -
Takayasu Fuchida,
Sadayuki Murashima,
Hirofumi Nakamura
Publication year - 2005
Publication title -
japan journal of industrial and applied mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 28
eISSN - 1868-937X
pISSN - 0916-7005
DOI - 10.1007/bf03167438
Subject(s) - voronoi diagram , fractal compression , fractal , image (mathematics) , domain (mathematical analysis) , range (aeronautics) , fractal transform , limit (mathematics) , pixel , compression (physics) , image compression , algorithm , process (computing) , mathematics , computer science , artificial intelligence , image processing , geometry , mathematical analysis , physics , materials science , composite material , thermodynamics , operating system
In this paper, we propose a new way of limiting the number of candidates of domains by using the shrunken image for Voronoi-based fractal image compression. And we show the result of computer simulations and confirm the effects of the proposed method. The process of domain search is the most critical process of fractal image compression because it takes exorbitant time to perform it. In the process of domain search, we have to use the term of Σr i , Σ di, Σr i 2, Σ di2 and Σr i d i , wherer i is the sum of pixels for the ith range andd i is same one for the corresponding domain. We can calculate these terms by using cumulations for the rectangular range, but for the Voronoi range, since the shape of a range is different from each other, we can not use the cumulations for calculating these terms. Therefore, it is necessary to limit the number of candidates of domains for finding the appropriate domain in order to reduce the time of compressing image.
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