Index 4.5 of /~cheungzhuo/fourththirdpart(KinLik)

Ranfoto1k HTMLfoto Ranfoto11k HTMLfoto1 Ranfoto21k HTMLfoto2 Ranphoto1k HTMLphoto and view 1, and view 2, and view 3, and view 4, andview 5, and view 6, and view 7, and view 8, and view 9, 10: (Winter 2005) , andScenery and diaryEarly Summer 2005, and 11: (early Summer 2006)

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 Name           
Last modified       Size  Description

 Lec : P intro.        26-May-2000 14:00      -  
 Lec : Japanese 2P intro.        26-May-2000 14:00      -  
 colour version.        2-May-2000 14:00      -  
 Lec : Japanese 3P intro.        26-May-2000 14:00      -  
 Lec : Japanese 4pieces.        26-May-2000 14:00      -  
 Lec : Chinese intro 

8pieces.        26-May-2000 14:00      -  
 

riverside.        2-May-2000 14:00      -  
 river 

play.        2-May-2000 14:00      -  
 river play 

2.        2-May-2000 14:00      -  
 big 

face.        2-May-2000 14:00      -  
 PREPICS  

17-Jul-00 11:58  1k  HTML Text
 SECONDPIC2S  17-Jul-00 11:58  1k  HTML2Text
 3rdPIC3S 

 18-Jul-00 11:58  1k  HTML3Text
 MOREPIC4,17-Jul-00 11:58 1k HTMLText4
  MOREPIC5,17-Jul-00 11:58 1k HTMLText5
 MOREPIC6,17-Jul-00 11:58 1k HTMLText64thPICS  

18-Jul-00 11:58  1k  HTML4Text

Image Table 2.4 - Results of the Extrapolation Algorithms for Still image and Actual (Higher-Level) Compression The results present the zeroth-order entropy of the prediction algorithms, the number of elevation corrections and its range, the percentage of DEM vertices that are predicted to within 0, 1, 2, and 5 metres, and the actual compressed code length using a higher order Arithmetic coding scheme. From this table, it can be deduced that the larger neighbourhoods of vertices that are used within the prediction process will produce better performance, but when large neighbourhoods are used (e.g., 24 points), the additional processing time does not necessarily warrant the very small improvements. The results also indicate that a poor predictor can be redeemed by a good higher order statistical encoding algorithm. For example, the vertical predictor performs worse than the linear predictor (by about 1 bpe), but after Arithmetic Coding, the results are better for the vertical predictor. In this instance, Arithmetic Coding uses row-wise data (in the x-plane) which when combined with the vertical predictor (in the y-plane) is equivalent to the linear (xy-plane) predictor. There is no doubt further room for improvement with respect to the use of dynamic predictors and the flexibility of statistical data compression algorithms exist; however, the result of under 1.6 bpe for this DEM represents a storage saving in excess of 90% over the traditional 2-byte integer, and is significantly better than the 4.164 bpe, which GZIP could only manage.
Today count. directory. KinLik, JFrancis, CUHKELE1984-1988 Joint Web.

KinLik's Bests 1984-2000 hkculture@yahoo.com.cn Port 80