Name
Abstract | ||
|---|---|---|
Predictive coders that split the prediction decision into con- texts depending on the local image behaviour have proved to be practically useful and successful in image coding appli- cations. Such predictive coders can be named as multi- channel. LOCO is a simple, yet successful example of such coders. Due to its success, a fair amount of attention has been paid for the improvement of multichannel predictive coders. The common task for these coders is to split the pixel layout around the pixel of interest into a list of contexts or prediction rules that specifically succeeds in predicting the value in a reasonable way. The improvement proposed in this work is due to the well known observation that the pre- diction error pdfs are not identically or evenly distributed for each channel output. Although several methods have been proposed for the compensation of this situation, they mostly perturb the low complexity behaviour. In this work, it is shown that a two-pass coder is a simple, yet efficient im- provement that perfectly determines channel pdf bias amounts, and the adjustment produces up to 5% compres- sion improvement over the test images. |
Year | Venue | Field |
|---|---|---|
2006 | EUSIPCO | Sharpening,Mean squared prediction error,Computer science,Communication channel,Image coding,Speech recognition,Pixel |
DocType | Citations | PageRank |
Conference | 1 | 0.41 |
References | Authors | |
2 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cihan Topal | 1 | 238 | 22.30 |
| Ömer Nezih Gerek | 2 | 118 | 19.51 |