Multi-sensor data fusion of VNIR and TIR satellite imagery

In this paper, we study the data fusion of visible and near infrared (VNIR) and thermal infrared (TIR) imagery. VNIR image gives high spatial resolution and clear edge expression information while TIR image gives Earth's surface temperature information. Frequently, it is not easy to utilize the TIR images in many remote sensing applications, because the TIR images does not have a good spatial resolution enough to describe spatial details. Thus, in order to improve the TIR image's availability and utilization, a multi-sensor data fusion of TIR and VNIR is quite necessary. In this paper, we have proposed an efficient way to fuse the VNIR and TIR images of Landsat 5 TM and ASTER. The panchromatic images is generated by using principal component analysis (PCA) from multi-spectral images, and the fused image is created by merging the panchromatic and thermal images. And finally, the performance test of the proposed fusion method is performed by using entropy concept. The method can be applied to detect hot-spot area such as forest fire and investigate a nuclear test and a surface temperature change in urban area.