Name
Abstract | ||
|---|---|---|
In this paper we describe an approximation of speckled image observation (attachment to data) laws by generalized gaussian pdfs. We use Kullback-Leibler (KL) divergence (entropy) for this purpose. This leads to a mathematical model which can be useful for speckled image restoration and for related hyperparamater estimation. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ISSPA.2003.1224731 | SEVENTH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, VOL 1, PROCEEDINGS |
Keywords | Field | DocType |
speckle,image restoration,context modeling,kullback leibler divergence,entropy,stochastic processes,kullback leibler,mathematical model,bismuth,markov processes,parameter estimation | Random field,Markov process,Pattern recognition,Hyperparameter,Markov random field,Markov chain,Gaussian,Artificial intelligence,Image restoration,Mathematics,Kullback–Leibler divergence | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emmanuel Bratsolis | 1 | 1 | 1.50 |
| Marc Sigelle | 2 | 316 | 34.12 |