The paper summarizes three modes for the use of neural network regression to fuse remote sensing images

while proposing a new pansharpening method

based on neural network regression

to fuse thermal infrared(TIR) image and the panchromatic(Pan) image

which can hardly be done using traditional image fusion techniques. Extreme learning machine algorithm is applied to obtain the regression relationship between remote sensing data

in a rapid and efficient manner

while the pansharpening for TIR focus on the internal physical relations of pixel values recorded as an image

and aiming at a real improvement of the TIR data quality rather than a visual enhancement. TIR data synthesized by this new image fusion method is qualified to be used in physical models. This provides convenience for quantitative remote sensing applications. Experiments on ETM+ images prove the effectiveness of this approach which achieves fairly accurate results

while direct fusing mode achieves dissatisfactory results.