Volume XLII-2/W7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 941-947, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-941-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 941-947, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-941-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  13 Sep 2017

13 Sep 2017

HYPERSPECTRAL IMAGE SHARPENING BASED ON EHLERS FUSION

S. Xu and M. Ehlers S. Xu and M. Ehlers
  • Institute of Computer Science, Osnabrueck University, Wachsbleiche 27, 49090 Osnabrueck, Germany

Keywords: Data Fusion, Hyperspectral Image, Pansharpening, Ehlers Fusion, IHS Transform, High-Pass Filter, Band-Pass Filter

Abstract. As the application of hyperspectral images is increasing, many researchers attempt to extend existing pansharpening techniques to hyperspectral images. This paper focuses on the application of Ehlers fusion to hyperspectral image sharpening. Ehlers fusion involves two crucial algorithms: filter technique in the frequency domain and intensity transform. In this study, different filter types and intensity transform methods were analysed separately. With a combination of filter types and intensity transforms, the fusion procedure was implemented to test data sets. The spectral profiles of the pixels of the images were then used as a tool to control the quality of the fused image. Finally, the performance of Ehlers fusion is compared with Principle Component (PC) analysis, Gram-Schmidt transform (Gram-Schmidt), High-Pass Filtering in the spatial domain (HPF), and Wavelet Principal Component (Wavelet-PC) analysis using the same input data. The comparison shows that Ehlers high-pass filter fusion shows outstanding performance both on spatial enhancement and colour preservation.