Block Symmetry Predictor to Improve Fractal Image Compression - Al-ani, Ruaa;George, Loay
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Various compression methods have been proposed to achieve high compression ratios and high image qualities in low computation time. One of these methods is Fractal Image Compression. The basic idea of fractal image compression is the partitioning of input image into non-overlapping range blocks. For every range block a similar but larger domain block is found. The set of coefficients of mapping the domain blocks to the range block, using affain transform, is recorded as compression data. The compressed image data set is called the Iterated Function System (IFS) mapping set. Decoding process…mehr

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Produktbeschreibung
Various compression methods have been proposed to achieve high compression ratios and high image qualities in low computation time. One of these methods is Fractal Image Compression. The basic idea of fractal image compression is the partitioning of input image into non-overlapping range blocks. For every range block a similar but larger domain block is found. The set of coefficients of mapping the domain blocks to the range block, using affain transform, is recorded as compression data. The compressed image data set is called the Iterated Function System (IFS) mapping set. Decoding process applies the determined IFS transformations on any initial image, and the process is repeated many times till reaching the attractor.
Autorenporträt
Name: Ruaa Abdullah JaberBirth: 1985Live in Iraq- BaghdadB.Sc. 2006M.Sc. 2009Work at (AL-Nahrain University/ College of Science/ Department of Compter Science) as a Lecturer Assistant