Paper Info
Title
Fusion and classification of synthetic aparture radar and multispectral sattellite data
Abstract
In this study, synthetic aperture radar (SAR) and multispectral data are fused with different methods in order to observe the effect of fusion methods on the accuracy of different classification techniques. At the same time, different polarizations of SAR data are included in fusion process and results are examined. The fusion methods that are used in this study are Brovey Color Normalized, Hue Saturation Value (HSV), Gram - Schmidt (GS) Spectral Sharpening and Principal Components (PC) Spectral Sharpening. Fused images are classified using k-nearest neighbor, support vector machine and radial based function neural network. The study area is chosen on Menemen Plain, which contains agricultural lands, and it is located in İzmir. Multispectral RapidEye satellite image and TerraSAR-X radar data are used for the analysis. Achieved results were presented in the tables. The highest accuracy is achieved by K-NN classification of TerraSAR-X and VH fusion with GS method as 95.74%.
Year
DOI
Venue
2014
10.1109/SIU.2014.6830339
Signal Processing and Communications Applications Conference
Keywords
Field
DocType
geophysical image processing,image classification,image colour analysis,image fusion,radial basis function networks,remote sensing by radar,support vector machines,synthetic aperture radar,transforms,Brovey color normalized,Gram-Schmidt spectral sharpening,HSV,İzmir,K-NN classification,Menemen Plain,SAR data polarizations,TerraSAR-X radar data,agricultural lands,hue saturation value,k-nearest neighbor,multispectral RapidEye satellite image,multispectral satellite data classification,multispectral satellite data fusion,principal components spectral sharpening,radial based function neural network,support vector machine,synthetic aperture radar classification,synthetic aperture radar fusion,Synthetic aperture radar,classification,fusion,multispectral
Sharpening,Radar,Computer vision,Image fusion,Pattern recognition,Computer science,Synthetic aperture radar,Multispectral image,Support vector machine,Artificial intelligence,Contextual image classification,Principal component analysis
Conference
ISSN
Citations 
PageRank 
2165-0608
0
0.34
References 
Authors
2
4
Name
Order
Citations
PageRank
Bakirman, T.100.34
Gökhan Bilgin26213.18
Fusun Balik Sanli384.51
Uslu, E.401.01