Abstract：How to use wavelet transform technology to extract information from remote sensing FTIR spectra, which were weak or always interfered by others, was described in the present paper. The Mexican hat function was used as a wavelet function to continuously transform the signals of pｕre chloroform, pｕre acetone and their mixture. The results indicated that the small scales were the ｇｕarantee of the accｕracｙ of correspondinｇ position between maｘimｕm modｕle of wavelet transform coefficients and break points of peaｋs． However，onlｙ one scale coｕld not determine the position of breaｋ point becaｕse of the effect of noise in small scales． On the contrarｙ，maｘimｕm modｕle of wavelet transform coefficients was relativelｙ stable in larｇe scales when noise was smoothed． Bｕt smoothness alwaｙs broｕｇht deviation of orientation． Therefore，mｕlti-scales shoｕld be combined to observe the breaｋ points of signals when ｕsinｇ wavelet transform technology． All in all，the breaｋ points of siｇnals coｕld be determined accｕratelｙ and stablｙ bｙ the wavelet transform technoloｇｙ and useful information was extracted. The signals were smoothed and magnified at the same time. According to the analysis of maximum module of wavelet transform coefficients and their orientation in different scales, some spectra, such as mixed and non-strongly-overlapped remote sensing FTIR spectra, could be recognized magnificently.
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