[Using wavelet transform for information extraction from remote sensing FTIR spectra].
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.
Liu
Fang
F
Advanced Spectroscopy Laboratory of College of Chemistry and Chemical Engineering, Nanjing University of Science & Technology, Nanjing 210014, China.
Wang
Jun-De
JD