URBAN FEATURES CLASSIFICATION USING 3D HYPERSPECTRAL DATA

被引：0

作者：

Shimoni, Michal ^{[1
]}

Idrissa, Mahamadou ^{[1
]}

Borghys, Dirk ^{[1
]}

Haavardsholm, Trym ^{[2
]}

Opsahl, Thomas-Olsvik ^{[2
]}

Perneel, Christiaan ^{[3
]}

机构：

[1] Belgian Royal Mil Acad SIC RMA, Signal & Image Ctr, 30 Ave Renaissance, Brussels, Belgium

[2] Norwegian Def Res Estab FFI, N-2027 Kjeller, Norway

[3] Belgian Royal Mil Acad, Dept Math, Brussels, Belgium

来源：

2013 5TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS) | 2013年

关键词：

Hyperspectral; Disparity map; Markov Random Field; Support Vector Machine; Stochastic Expectation Maximization;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The surface classification of heterogeneous urban areas can be refined using the integration of spectral and 3D information. However, pixel-classification based fusion requires semi-pixel geo-registration accuracy. In this paper the 3D information is obtained from the hyperspectral data set itself. This study presents an adaptation of optimized MRF based stereo matching for the creation of 3D scenes using hyperspectral data. The obtained 3D information is integrated into a SVM classifier procedure. The results obtained in this study show the potential in the creation of 3D scenes using hyperspectral data and the benefit of combining this data with spectral information for better classification of the urban materials.

引用

页数：4

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