Name
Abstract | ||
|---|---|---|
A coarse-classification based tying method for the Contourlet-domain Hidden Markov Tree model (CHMT) solution algorithm is proposed to speed up the parameters estimation; and a general SAR image filtering framework, to which any kind of shift-variant transform can be applied, is generated by applying together with the LOG Transform, mean rectification and cycle-spinning, etc. The proposed coarse classification based tying method for CHMT is applied to de-speckle the SAR image in the general framework, and the result is compared with those of some commonly-used filters. The visual effects and the statistical parameters indicate that the coarse-classification based tying method for CHMT is much faster than the other tying methods, and the CHMT based de-speckle method can achieve better result than some commonly-used filters. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/IGARSS.2010.5653521 | IGARSS |
Keywords | Field | DocType |
synthetic aperture radar,parameters estimation,contourlet transform,hidden markov tree,sar image filtering,speckle,image classification,filtering theory,filtering,chmt model,coarse-classification based tying method,statistical parameters,radar imaging,hidden markov models,despeckling method,contourlet-domain hidden markov tree model,classification algorithms,noise,wavelet transforms,parameter estimation | Statistical parameter,Computer vision,Pattern recognition,Computer science,Synthetic aperture radar,Filter (signal processing),Artificial intelligence,Hidden Markov model,Contextual image classification,Statistical classification,Contourlet,Wavelet transform | Conference |
ISSN | ISBN | Citations |
2153-6996 E-ISBN : 978-1-4244-9564-1 | 978-1-4244-9564-1 | 0 |
PageRank | References | Authors |
0.34 | 7 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Deng | 1 | 15 | 6.53 |
| Wenji Zhao | 2 | 25 | 17.51 |
| Deyong Hu | 3 | 21 | 5.90 |
| Zhuowei Hu | 4 | 6 | 6.10 |
| Gaoming Cao | 5 | 0 | 0.34 |