Volume XL-7/W1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W1, 33-36, 2013
https://doi.org/10.5194/isprsarchives-XL-7-W1-33-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W1, 33-36, 2013
https://doi.org/10.5194/isprsarchives-XL-7-W1-33-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

  12 Jul 2013

12 Jul 2013

IMAGE FUSION AND IMAGE QUALITY ASSESSMENT OF FUSED IMAGES

Z. Han1, X. Tang2, X. Gao2, and F. Hu2 Z. Han et al.
  • 1School of Mapping And Geographic Information Systems, Lanzhou Jiao Tong University, China
  • 2Satellite Surveying and Mapping Application Centre, NASG, China

Keywords: Image Fusion, Brovey, PCA, Pansharp, SFIM, Accuracy Evaluation

Abstract. It is of great value to fuse a high-resolution panchromatic image and low-resolution multi-spectral images for object recognition. In the paper, tow frames of remotely sensed imagery, including ZY03 and SPOT05, are selected as the source data. Four fusion methods, including Brovey, PCA, Pansharp, and SFIM, are used to fuse the images of multispectral bands and panchromatic band. Three quantitative indicators were calculated and analyzed, that is, gradient, correlation coefficient and deviation. According to comprehensive evaluation and comparison, the best effect is SFIM transformation, combined with fusion image through four transformation methods.