Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 961-965, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-961-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 961-965, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-961-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

MULTISPECTRAL PANSHARPENING APPROACH USING PULSE-COUPLED NEURAL NETWORK SEGMENTATION

X. J. Li1,2, H. W. Yan1,2, S. W. Yang1,2, L. Kang1,2, and X. M. Lu1,2 X. J. Li et al.
  • 1Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou, China
  • 2Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou, China

Keywords: Pansharpening, PCNN, Image Fusion, Multispectral Imaging, Remote Sensing, Segmentation

Abstract. The paper proposes a novel pansharpening method based on the pulse-coupled neural network segmentation. In the new method, uniform injection gains of each region are estimated through PCNN segmentation rather than through a simple square window. Since PCNN segmentation agrees with the human visual system, the proposed method shows better spectral consistency. Our experiments, which have been carried out for both suburban and urban datasets, demonstrate that the proposed method outperforms other methods in multispectral pansharpening.