Optical near-field data analysis through time-frequency distributions: application to the characterization and...

The near-field optical images have been traditionally analyzed by Fourier analysis and, recently, by wavelet analysis. Those data are nonstationary, which means that their spectral content varies with time, owing to the scanning-probe recording process; therefore time-frequency representations are, potentially, powerful tools for local characteristics extraction or shape separation, since they distribute the energy of the analyzed signal over the time and frequency variables and faithfully depict the signal local behavior. In this study we show that Cohen's class time-frequency distributions and their modified version by the reassignment method are appropriate tools for the analysis of near-field optical data. We demonstrate this by using these tools first on simulated data and second on experimental near-field optical images. Within this context we observe that time-frequency analysis allows one to easily characterize local frequencies, which involves a possible separation of relevant optical signal from artifacts.