Bag-of-Visual-Words Model for Classification of Interferometric SAR Images
Konferenz: EUSAR 2016 - 11th European Conference on Synthetic Aperture Radar
06.06.2016 - 09.06.2016 in Hamburg, Germany
Tagungsband: EUSAR 2016
Seiten: 4Sprache: EnglischTyp: PDFPersönliche VDE-Mitglieder erhalten auf diesen Artikel 10% Rabatt
Cagatay, Nazli Deniz; Datcu, Mihai (German Aerospace Center (DLR), Germany)
This work introduces a well-accepted image representation model in image analysis, namely the Bag-of-Visual-Words (BoVW), to interferometric SAR (InSAR) images. As the low-level local features, Gabor- and fractional Fourier transform (FrFT)-based feature descriptors are used. The supervised classification results with BoVW-Gabor and BoVW-FrFT features are compared to those with global Gabor and global FrFT features. Although the global Gabor features are better than the global FrFT features, by the implementation of BoVW model, FrFT outperforms Gabor features. Also, the classification performances of different baseline acquisitions for the same scenes are compared. For each baseline, the mean and individual class accuracies are improved by using BoVW-FrFT features.