
Proceedings Paper
Application and evaluation of ISVR method in QuickBird image fusionFormat | Member Price | Non-Member Price |
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Paper Abstract
QuickBird satellite images are widely used in many fields, and applications have put forward high requirements for the
integration of the spatial information and spectral information of the imagery. A fusion method for high resolution
remote sensing images based on ISVR is identified in this study. The core principle of ISVS is taking the advantage of
radicalization targeting to remove the effect of different gain and error of satellites’ sensors. Transformed from DN to
radiance, the multi-spectral image’s energy is used to simulate the panchromatic band. The linear regression analysis is
carried through the simulation process to find a new synthetically panchromatic image, which is highly linearly
correlated to the original panchromatic image. In order to evaluate, test and compare the algorithm results, this paper
used ISVR and other two different fusion methods to give a comparative study of the spatial information and spectral
information, taking the average gradient and the correlation coefficient as an indicator. Experiments showed that this
method could significantly improve the quality of fused image, especially in preserving spectral information, to
maximize the spectral information of original multispectral images, while maintaining abundant spatial information.
Paper Details
Date Published: 14 May 2014
PDF: 6 pages
Proc. SPIE 9158, Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, 915802 (14 May 2014); doi: 10.1117/12.2063895
Published in SPIE Proceedings Vol. 9158:
Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China
Qingxi Tong; Jie Shan; Boqin Zhu, Editor(s)
PDF: 6 pages
Proc. SPIE 9158, Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, 915802 (14 May 2014); doi: 10.1117/12.2063895
Show Author Affiliations
Bo Cheng, Institute of Remote Sensing and Digital Earth (China)
Xiaolu Song, Univ. of Chinese Academy of Sciences (China)
Published in SPIE Proceedings Vol. 9158:
Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China
Qingxi Tong; Jie Shan; Boqin Zhu, Editor(s)
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