Name
Title | ||
|---|---|---|
Unsupervised classification of radar images using hidden Markov chains and hidden Markov random fields |
Abstract | ||
|---|---|---|
Due to the enormous quantity of radar images acquired by satellites and through shuttle missions, there is an evident need for efficient automatic analysis tools. This paper describes unsupervised classification of radar images in the framework of hidden Markov models and generalized mixture estimation. Hidden Markov chain models, applied to a Hilbert-Peano scan of the image, constitute a fast and... |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/TGRS.2003.809940 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | DocType | Volume |
Hidden Markov models,Radar imaging,Image analysis,Reflectivity,Speckle,Stochastic processes,Iterative methods,Gaussian distribution,Radar remote sensing,Satellites | Journal | 41 |
Issue | ISSN | Citations |
3 | 0196-2892 | 63 |
PageRank | References | Authors |
5.15 | 13 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| R. Fjortoft | 1 | 234 | 27.36 |
| Yves Delignon | 2 | 164 | 16.55 |
| Wojciech Pieczynski | 3 | 142 | 12.93 |
| Marc Sigelle | 4 | 316 | 34.12 |
| Florence Tupin | 5 | 1322 | 109.27 |