Name
Abstract | ||
|---|---|---|
In this paper we introduce a new class of adaptive nonlinear predictors by allowing the parameters of the L-predictor to be selected according to the transitions in a finite state machine (FSM) context modeller. A procedure for the adaptive design of the general unconstrained FSM-context L-predictor is proposed and compared with the classical design techniques for some particular FSM-L predictors. The application of the new predictor for lossless compression of gray level images is examined for different FSM structures. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1109/ICIP.1997.647791 | ICIP (1) |
Keywords | Field | DocType |
general unconstrained fsm-context l-predictor,classical design technique,gray level image,finite state machine,different fsm structure,adaptive nonlinear predictor,finite state machine context,new class,adaptive design,context modeller,new predictor,adaptive signal processing,predictive models,context modeling,adaptive filters,pixel,finite state machines,statistics,lossless compression,automata,data compression | Adaptive design,Nonlinear system,Computer science,Image coding,Finite-state machine,Theoretical computer science,Gray level,Adaptive filter,Data compression,Lossless compression | Conference |
ISBN | Citations | PageRank |
0-8186-8183-7 | 4 | 0.75 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| I. Tabus | 1 | 87 | 10.32 |
| Jorma Rissanen | 2 | 1665 | 798.14 |
| J. Astola | 3 | 1174 | 138.74 |