Spatial hyperspectral image classification by prior segmentation

Publication Type:

Conference Paper


Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009, Volume 3, Cape Town, South Africa, p.III-709 - III-712 (2009)



Accession Number:



Belgium, geophysical image processing, heathland area, hyperspectral data classification, image classification, image segmentation, prior segmentation, remote sensing, spatial hyperspectral image classification, spatially smoothed regions, spectral classification


In this paper, we propose a technique to incorporate spatial features in the classification of hyperspectral data by means of a prior segmentation of the dataset. The key idea of the technique is that each pixel is not classified individually, but that the regions obtained from the prior segmentation are classified as a whole. The proposed technique is validated on a hyperspectral dataset of a heathland area in Belgium. Experimental results show that we can achieve larger and spatially smoothed regions, while the overall classification success rate is comparable to the pure spectral classification results.

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