The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XXXIX-B7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B7, 387–392, 2012
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B7, 387–392, 2012

  01 Aug 2012

01 Aug 2012


C. Chisense, J. Engels, M. Hahn, and E. Gülch C. Chisense et al.
  • Stuttgart University of Applied Sciences Schellingstr. 24 D-70174 Stuttgart, Germany

Keywords: image fusion, hyperspectral, resolution, urban, classification

Abstract. Pansharpening has proven to be a valuable method for resolution enhancement of multi-band images when spatially high-resolving panchromatic images are available in addition. In principle, pansharpening can beneficially be applied to hyperspectral images as well. But whereas the grey values of multi-spectral images comprise at most relative information about the registered intensities, calibrated hyperspectral images are supposed to provide absolute reflectivity values of the respective material surfaces. This physical significance of the hyperspectral data should be preserved within the pansharpening process as much as possible. In this paper we compare several common pansharpening methods such as Principal Component Fusion, Wavelet Fusion, Gram-Schmidt transform and investigate their applicability for hyperspectral data. Our focus is on the impact of the pansharpening on material classifications. Apart from applying common quality measures, we compare the results of material classifications from hyperspectral data, which were pansharpened by different methods. In addition we propose an alternative pansharpening method which is based on an initial segmentation of the panchromatic image with an additional use of map vector data.