Application and evaluation of ISVR method in QuickBird image fusion

Bo Cheng; Xiaolu Song

doi:10.1117/12.2063895

14 May 2014 Application and evaluation of ISVR method in QuickBird image fusion

Bo Cheng, Xiaolu Song

Proceedings Volume 9158, Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China; 915802 (2014) https://doi.org/10.1117/12.2063895
Event: Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, 2012, Wuhan, China

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.

Citation Download Citation

Bo Cheng and Xiaolu Song "Application and evaluation of ISVR method in QuickBird image fusion", Proc. SPIE 9158, Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, 915802 (14 May 2014); https://doi.org/10.1117/12.2063895

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KEYWORDS

Image fusion

Remote sensing

Image enhancement

Image quality

Multispectral imaging

Image resolution

Calibration

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