A technique based on non-linear transform and multivariate analysis to merge thermal infrared data and higher-resolution multispectral data

Abstract

A thermal infrared (TIR) image is a measure of the Earth's surface temperature and TIR emittance; however, its low spatial resolution severely limits its potential applications. Image fusion techniques can be used to fuse a TIR image with higher spatial resolution reflective bands to generate a synthetic TIR image. Because of the weak correlation between TIR and reflective data, such a synthetic image typically contains significant spectral distortion. In this paper, a multivariate analysis technique is used to derive a variable as a linear function of multiple reflective bands and their non-linearly transformed versions, to produce the maximum correlation with the TIR image. The spatial details of the variable are then injected into the TIR image to yield a synthetic image with reduced spectral distortion. In an experiment on Landsat Thematic Mapper (TM) TIR and reflective data, the fusion method proposed in this paper outperforms several existing methods in preserving the spectral characteristics of TIR data.

Acknowledgements

This research was jointly supported by the National Natural Science Foundation of China (Grants 40525009 and 40638041), the Ministry of Education of China (No. 104244, No. IRT0755), and the Chinese ‘863’ project (2006AA06Z115). We thank two anonymous referees for their constructive comments.