|
|
|
|
LEADER |
01000caa a22002652 4500 |
001 |
NLM177695722 |
003 |
DE-627 |
005 |
20250209060230.0 |
007 |
tu |
008 |
231223s1997 xx ||||| 00| ||eng c |
028 |
5 |
2 |
|a pubmed25n0592.xml
|
035 |
|
|
|a (DE-627)NLM177695722
|
035 |
|
|
|a (NLM)18282913
|
040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
041 |
|
|
|a eng
|
100 |
1 |
|
|a Hu, J H
|e verfasserin
|4 aut
|
245 |
1 |
0 |
|a Multispectral code excited linear prediction coding and its application in magnetic resonance images
|
264 |
|
1 |
|c 1997
|
336 |
|
|
|a Text
|b txt
|2 rdacontent
|
337 |
|
|
|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
|
338 |
|
|
|a Band
|b nc
|2 rdacarrier
|
500 |
|
|
|a Date Completed 02.10.2012
|
500 |
|
|
|a Date Revised 19.02.2008
|
500 |
|
|
|a published: Print
|
500 |
|
|
|a Citation Status PubMed-not-MEDLINE
|
520 |
|
|
|a This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256x256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously
|
650 |
|
4 |
|a Journal Article
|
700 |
1 |
|
|a Wang, Y
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Cahill, P T
|e verfasserin
|4 aut
|
773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 6(1997), 11 vom: 15., Seite 1555-66
|w (DE-627)NLM09821456X
|x 1057-7149
|7 nnns
|
773 |
1 |
8 |
|g volume:6
|g year:1997
|g number:11
|g day:15
|g pages:1555-66
|
912 |
|
|
|a GBV_USEFLAG_A
|
912 |
|
|
|a SYSFLAG_A
|
912 |
|
|
|a GBV_NLM
|
912 |
|
|
|a GBV_ILN_350
|
951 |
|
|
|a AR
|
952 |
|
|
|d 6
|j 1997
|e 11
|b 15
|h 1555-66
|