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231223s1998 xx |||||o 00| ||eng c |
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|a 10.1109/83.725366
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|a eng
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| 100 |
1 |
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|a Kim, C S
|e verfasserin
|4 aut
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| 245 |
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|a A fractal vector quantizer for image coding
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|c 1998
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|a Text
|b txt
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|a ƒaComputermedien
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|a Date Completed 14.12.2009
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|a Date Revised 15.02.2008
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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|a We investigate the relation between VQ (vector quantization) and fractal image coding techniques, and propose a novel algorithm for still image coding, based on fractal vector quantization (FVQ). In FVQ, the source image is approximated coarsely by fixed basis blocks, and the codebook is self-trained from the coarsely approximated image, rather than from an outside training set or the source image itself. Therefore, FVQ is capable of eliminating the redundancy in the codebook without any side information, in addition to exploiting the self-similarity in real images effectively. The computer simulation results demonstrate that the proposed algorithm provides better peak signal-to-noise ratio (PSNR) performance than most other fractal-based coders
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|a Letter
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|a Kim, R C
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Lee, S U
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 7(1998), 11 vom: 30., Seite 1598-602
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|x 1057-7149
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|u http://dx.doi.org/10.1109/83.725366
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