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231223s1997 xx ||||| 00| ||eng c |
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|a pubmed25n0592.xml
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|a (DE-627)NLM177696079
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|a (NLM)18282949
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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 Abousleman, G P
|e verfasserin
|4 aut
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|a Hyperspectral image compression using entropy-constrained predictive trellis coded quantization
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|c 1997
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|a Text
|b txt
|2 rdacontent
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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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|a Date Revised 19.02.2008
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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|a A training-sequence-based entropy-constrained predictive trellis coded quantization (ECPTCQ) scheme is presented for encoding autoregressive sources. For encoding a first-order Gauss-Markov source, the mean squared error (MSE) performance of an eight-state ECPTCQ system exceeds that of entropy-constrained differential pulse code modulation (ECDPCM) by up to 1.0 dB. In addition, a hyperspectral image compression system is developed, which utilizes ECPTCQ. A hyperspectral image sequence compressed at 0.125 b/pixel/band retains an average peak signal-to-noise ratio (PSNR) of greater than 43 dB over the spectral bands
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|a Journal Article
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|a Marcellin, M W
|e verfasserin
|4 aut
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|a Hunt, B R
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 6(1997), 4 vom: 15., Seite 566-73
|w (DE-627)NLM09821456X
|x 1057-7149
|7 nnns
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| 773 |
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|g volume:6
|g year:1997
|g number:4
|g day:15
|g pages:566-73
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|a GBV_USEFLAG_A
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|a SYSFLAG_A
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|a GBV_NLM
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|a GBV_ILN_350
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|a AR
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|d 6
|j 1997
|e 4
|b 15
|h 566-73
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