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231223s1995 xx ||||| 00| ||eng c |
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|a pubmed25n0593.xml
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|a (DE-627)NLM177764155
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|a (NLM)18290051
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Liang, K M
|e verfasserin
|4 aut
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| 245 |
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|a Comparison between adaptive search and bit allocation algorithms for image compression using vector quantization
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|c 1995
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| 336 |
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|a Text
|b txt
|2 rdacontent
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| 337 |
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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| 338 |
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 02.10.2012
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| 500 |
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|a Date Revised 21.02.2008
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| 500 |
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a This article discusses bit allocation and adaptive search algorithms for mean-residual vector quantization (MRVQ) and multistage vector quantization (MSVQ). The adaptive search algorithm uses a buffer and a distortion threshold function to control the bit rate that is assigned to each input vector. It achieves a constant rate for the entire image but variable bit rate for each vector in the image. For a given codebook and several bit rates, we compare the performance between the optimal bit allocation and adaptive search algorithms. The results show that the performance of the adaptive search algorithm is only 0.20-0.53 dB worse than that of the optimal bit allocation algorithm, but the complexity of the adaptive search algorithm is much less than that of the optimal bit allocation algorithm
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| 650 |
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|a Journal Article
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| 700 |
1 |
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|a Huang, C M
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Harris, R W
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 4(1995), 7 vom: 15., Seite 1020-3
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnas
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| 773 |
1 |
8 |
|g volume:4
|g year:1995
|g number:7
|g day:15
|g pages:1020-3
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|a GBV_USEFLAG_A
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|a GBV_ILN_350
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| 951 |
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|a AR
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| 952 |
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|d 4
|j 1995
|e 7
|b 15
|h 1020-3
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