Name
Abstract | ||
|---|---|---|
Two edge-preserving segmentation algorithms for multiband images are proposed in this paper. In particular, when dealing with multipolarization SAR data, adaptive neighborhood structures are selected for modelling polarimetric complex amplitudes and region labels, and for achieving detail-preservation. Experimental results show that the novel schemes produce significant visual improvements for detail preservation, and exhibit equivalent or higher classification performance with respect to the classical classification schemes. These results have been obtained from multiband, polarimetric SAR SIR-C data, selected for archaeological application studies |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1109/ICIP.1996.560936 | ICIP (3) |
Keywords | Field | DocType |
sar sir-c data,multiband images,synthetic aperture radar,multifrequency multipolarization data,edge-preserving classification,region labels,image segmentation,edge-preserving segmentation algorithms,adaptive neighborhood structures,archaeological application,image classification,edge detection,radar imaging,polarimetric complex amplitudes,radar polarimetry,detail preservation,sar images,context modeling,testing,maximum likelihood estimation,layout,scattering | Computer vision,Radar imaging,Scale-space segmentation,Pattern recognition,Computer science,Synthetic aperture radar,Edge detection,Segmentation,Inverse synthetic aperture radar,Image segmentation,Artificial intelligence,Contextual image classification | Conference |
Volume | ISBN | Citations |
3 | 0-7803-3259-8 | 0 |
PageRank | References | Authors |
0.34 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessandro Andreadis | 1 | 37 | 10.36 |
| Giuliano Benelli | 2 | 41 | 15.13 |
| Andrea Garzelli | 3 | 574 | 41.36 |