The infrared channel of geostationary satellites can detect weak texture information resulting from the u neven distribution of atmospheric water vapor and dust aerosol in cloud-free regions. Atmospheric Motion Vectors（ AMVs） for cloud-free regions can be retrieved by tracking water vapor motion or dust aerosol motion. However

weak information is easily affected by changes in surface temperature. Therefore

a suitable algorithm must be developed to decrease surface temperature interference and to extract weak information. Basing on split-window infrared theory

we perform a numerical simulation of extracting weak information by using the split-window Brightness Temperature Difference（ BTD） algorithm. We also apply this algorithm to instance analysis. The numerical study indicates that u sing BTD images can weaken the influence of surface temperature and highlight the distribution characteristics of water vapor and aerosol. It also explains the feasibility and superiority of this algorithm. In cloud-free regions

low-level wind that is hard to obtain by only using IR1 or IR2 images can be obtained by using BTD images. The results of the cases agree with the wind field of the NCEP reanalysis data.